- Julien Mairal, Rodolphe Jenatton, Guillaume Obozinski, Francis R. Bach:
Convex and Network Flow Optimization for Structured Sparsity. Journal of Machine Learning Research 12: 2681-2720 (2011) - Huixin Wang, Xiaotong Shen, Wei Pan:
Large Margin Hierarchical Classification with Mutually Exclusive Class Membership. Journal of Machine Learning Research 12: 2721-2748 (2011) - Elias Zavitsanos, Georgios Paliouras, George A. Vouros:
Non-Parametric Estimation of Topic Hierarchies from Texts with Hierarchical Dirichlet Processes. Journal of Machine Learning Research 12: 2749-2775 (2011) - Rodolphe Jenatton, Jean-Yves Audibert, Francis R. Bach:
Structured Variable Selection with Sparsity-Inducing Norms. Journal of Machine Learning Research 12: 2777-2824 (2011) - Fabian Pedregosa, Gaël Varoquaux, Alexandre Gramfort, Vincent Michel, Bertrand Thirion, Olivier Grisel, Mathieu Blondel, Peter Prettenhofer, Ron Weiss, Vincent Dubourg, Jake VanderPlas, Alexandre Passos, David Cournapeau, Matthieu Brucher, Matthieu Perrot, Edouard Duchesnay:
Scikit-learn: Machine Learning in Python. Journal of Machine Learning Research 12: 2825-2830 (2011) - Philippe Rigollet, Xin Tong:
Neyman-Pearson Classification, Convexity and Stochastic Constraints. Journal of Machine Learning Research 12: 2831-2855 (2011) - Nicolò Cesa-Bianchi, Shai Shalev-Shwartz, Ohad Shamir:
Efficient Learning with Partially Observed Attributes. Journal of Machine Learning Research 12: 2857-2878 (2011) - Adam D. Bull:
Convergence Rates of Efficient Global Optimization Algorithms. Journal of Machine Learning Research 12: 2879-2904 (2011) - Seyda Ertekin, Cynthia Rudin:
On Equivalence Relationships Between Classification and Ranking Algorithms. Journal of Machine Learning Research 12: 2905-2929 (2011) - Martijn R. K. Mes, Warren B. Powell, Peter I. Frazier:
Hierarchical Knowledge Gradient for Sequential Sampling. Journal of Machine Learning Research 12: 2931-2974 (2011) - Shuheng Zhou, Philipp Rütimann, Min Xu, Peter Bühlmann:
High-dimensional Covariance Estimation Based On Gaussian Graphical Models. Journal of Machine Learning Research 12: 2975-3026 (2011) - Marek Petrik, Shlomo Zilberstein:
Robust Approximate Bilinear Programming for Value Function Approximation. Journal of Machine Learning Research 12: 3027-3063 (2011) - Jan Saputra Müller, Paul von Bünau, Frank C. Meinecke, Franz J. Király, Klaus-Robert Müller:
The Stationary Subspace Analysis Toolbox. Journal of Machine Learning Research 12: 3065-3069 (2011) - Lucas Theis, Sebastian Gerwinn, Fabian H. Sinz, Matthias Bethge:
In All Likelihood, Deep Belief Is Not Enough. Journal of Machine Learning Research 12: 3071-3096 (2011) - Jianxin Wu, Wei-Chian Tan, James M. Rehg:
Efficient and Effective Visual Codebook Generation Using Additive Kernels. Journal of Machine Learning Research 12: 3097-3118 (2011) - Krishnakumar Balasubramanian, Pinar Donmez, Guy Lebanon:
Unsupervised Supervised Learning II: Margin-Based Classification Without Labels. Journal of Machine Learning Research 12: 3119-3145 (2011) - Özgür Sümer, Umut A. Acar, Alexander T. Ihler, Ramgopal R. Mettu:
Adaptive Exact Inference in Graphical Models. Journal of Machine Learning Research 12: 3147-3186 (2011) - Jérémie Bigot, Rolando J. Biscay, Jean-Michel Loubes, Lilian Muñiz-Alvarez:
Group Lasso Estimation of High-dimensional Covariance Matrices. Journal of Machine Learning Research 12: 3187-3225 (2011) - Pasi Jylänki, Jarno Vanhatalo, Aki Vehtari:
Robust Gaussian Process Regression with a Student-t Likelihood. Journal of Machine Learning Research 12: 3227-3257 (2011) - Daniel Vainsencher, Shie Mannor, Alfred M. Bruckstein:
The Sample Complexity of Dictionary Learning. Journal of Machine Learning Research 12: 3259-3281 (2011) - Piotr Zwiernik:
An Asymptotic Behaviour of the Marginal Likelihood for General Markov Models. Journal of Machine Learning Research 12: 3283-3310 (2011) - Amarnag Subramanya, Jeff A. Bilmes:
Semi-Supervised Learning with Measure Propagation. Journal of Machine Learning Research 12: 3311-3370 (2011) - Junzhou Huang, Tong Zhang, Dimitris N. Metaxas:
Learning with Structured Sparsity. Journal of Machine Learning Research 12: 3371-3412 (2011) - Benjamin Recht:
A Simpler Approach to Matrix Completion. Journal of Machine Learning Research 12: 3413-3430 (2011) - Benoît Patra:
Convergence of Distributed Asynchronous Learning Vector Quantization Algorithms. Journal of Machine Learning Research 12: 3431-3466 (2011) - W.-H. Kuo, D.-L. Yang:
A note on due-date assignment and single-machine scheduling with deteriorating jobs and learning effects. JORS 62(1): 206-210 (2011) - Loris Pignolo, Vincenzo i Lagan:
Prediction of Outcome in the Vegetative State by Machine Learning Algorithms: A Model for Clinicians? JSEA 4(6): 388-390 (2011) - Xiaoyuan Xie, Joshua W. K. Ho, Christian Murphy, Gail E. Kaiser, Baowen Xu, Tsong Yueh Chen:
Testing and validating machine learning classifiers by metamorphic testing. Journal of Systems and Software 84(4): 544-558 (2011) - Jelte Peter Vink, Gerard de Haan:
No-Reference Metric Design With Machine Learning for Local Video Compression Artifact Level. J. Sel. Topics Signal Processing 5(2): 297-308 (2011) - Chengjie Gu, Shunyi Zhang, Yanfei Sun:
Realtime Encrypted Traffic Identification using Machine Learning. JSW 6(6): 1009-1016 (2011) - Xiao-dan Zhang, De-gan Zhang, De-xin Zhao, Xuejing Kang, Xiao-dong Qiao:
A New Dynamic Method of Machine Learning From Transition Examples. JSW 6(10): 2064-2067 (2011) - Fengyi Lin, Ching-Chiang Yeh, Meng-Yuan Lee:
The use of hybrid manifold learning and support vector machines in the prediction of business failure. Knowl.-Based Syst. 24(1): 95-101 (2011) - D. Chandrakala, S. Sumathi, S. Karthi:
Optimized code matrix generation for classification of multi-class pattern recognition problems using machine learning techniques. KES Journal 15(4): 227-245 (2011) - Vincent Vandeghinste:
Learning Machine Translation.Cyril Goutte, Nicola Cancedda, Marc Dymetman, and George Foster. LLC 26(4): 484-486 (2011) - Edoardo Pasolli, Farid Melgani, Yakoub Bazi:
Support Vector Machine Active Learning Through Significance Space Construction. IEEE Geosci. Remote Sensing Lett. 8(3): 431-435 (2011) - Thomas Lavergne, Tanguy Urvoy, François Yvon:
Filtering artificial texts with statistical machine learning techniques. Language Resources and Evaluation 45(1): 25-43 (2011) - Ji-Bo Wang, Ming-Zheng Wang:
A revision of machine scheduling problems with a general learning effect. Mathematical and Computer Modelling 53(1-2): 330-336 (2011) - Yunqiang Yin, Dehua Xu:
Notes on "Single machine scheduling problems under the effects of nonlinear deterioration and time-dependent learning". Mathematical and Computer Modelling 54(1-2): 846-848 (2011) - M. Duran Toksari, Daniel Oron, Ertan Güner:
Joint reply to the erratum and the note on "Single machine scheduling problems under the effects of nonlinear deterioration and time-dependent learning" [Math. Comput. Modelling 50 (2009) 401-406]. Mathematical and Computer Modelling 54(1-2): 849-851 (2011) - María Araújo, T. Rivas, Eduardo Giráldez, Javier Taboada:
Use of machine learning techniques to analyse the risk associated with mine sludge deposits. Mathematical and Computer Modelling 54(7-8): 1823-1828 (2011) - Daria Dzyabura, John R. Hauser:
Active Machine Learning for Consideration Heuristics. Marketing Science 30(5): 801-819 (2011) - David Martens, Bart Baesens, Tom Fawcett:
Editorial survey: swarm intelligence for data mining. Machine Learning 82(1): 1-42 (2011) - Yanping Lu, Shengrui Wang, Shaozi Li, Changle Zhou:
Particle swarm optimizer for variable weighting in clustering high-dimensional data. Machine Learning 82(1): 43-70 (2011) - Luis Felipe Giraldo, Fernando Lozano, Nicanor Quijano:
Foraging theory for dimensionality reduction of clustered data. Machine Learning 82(1): 71-90 (2011) - S. V. N. Vishwanathan, Samuel Kaski, Jennifer Neville, Stefan Wrobel:
Introduction to the special issue on mining and learning with graphs. Machine Learning 82(2): 91-93 (2011) - Ichigaku Takigawa, Hiroshi Mamitsuka:
Efficiently mining δ-tolerance closed frequent subgraphs. Machine Learning 82(2): 95-121 (2011) - Elisabeth Georgii, Koji Tsuda, Bernhard Schölkopf:
Multi-way set enumeration in weight tensors. Machine Learning 82(2): 123-155 (2011) - Tianbao Yang, Yun Chi, Shenghuo Zhu, Yihong Gong, Rong Jin:
Detecting communities and their evolutions in dynamic social networks - a Bayesian approach. Machine Learning 82(2): 157-189 (2011) - Achim Rettinger, Matthias Nickles, Volker Tresp:
Statistical relational learning of trust. Machine Learning 82(2): 191-209 (2011) - Jie Tang, Jing Zhang, Ruoming Jin, Zi Yang, Keke Cai, Li Zhang, Zhong Su:
Topic level expertise search over heterogeneous networks. Machine Learning 82(2): 211-237 (2011) - Ingo Thon, Niels Landwehr, Luc De Raedt:
Stochastic relational processes: Efficient inference and applications. Machine Learning 82(2): 239-272 (2011) - Peter A. Flach:
The Machine Learning journal: 25 years young. Machine Learning 82(3): 273-274 (2011) - Jacob W. Crandall, Michael A. Goodrich:
Learning to compete, coordinate, and cooperate in repeated games using reinforcement learning. Machine Learning 82(3): 281-314 (2011) - Werner Uwents, Gabriele Monfardini, Hendrik Blockeel, Marco Gori, Franco Scarselli:
Neural networks for relational learning: an experimental comparison. Machine Learning 82(3): 315-349 (2011) - Alexander Clark, Christophe Costa Florêncio, Chris Watkins:
Languages as hyperplanes: grammatical inference with string kernels. Machine Learning 82(3): 351-373 (2011) - Kai Ming Ting, Jonathan R. Wells, Swee Chuan Tan, Shyh Wei Teng, Geoffrey I. Webb:
Feature-subspace aggregating: ensembles for stable and unstable learners. Machine Learning 82(3): 375-397 (2011) - Lihong Li, Michael L. Littman, Thomas J. Walsh, Alexander L. Strehl:
Knows what it knows: a framework for self-aware learning. Machine Learning 82(3): 399-443 (2011) - Saher Esmeir, Shaul Markovitch:
Anytime learning of anycost classifiers. Machine Learning 82(3): 445-473 (2011) - Jan Zahálka, Filip Zelezný:
An experimental test of Occam's razor in classification. Machine Learning 82(3): 475-481 (2011) - Chiaki Sakama, Katsumi Inoue:
Inductive equivalence in clausal logic and nonmonotonic logic programming. Machine Learning 83(1): 1-29 (2011) - Stéphan Clémençon, Marine Depecker, Nicolas Vayatis:
Adaptive partitioning schemes for bipartite ranking - How to grow and prune a ranking tree. Machine Learning 83(1): 31-69 (2011) - Giovanni Cavallanti, Nicolò Cesa-Bianchi, Claudio Gentile:
Learning noisy linear classifiers via adaptive and selective sampling. Machine Learning 83(1): 71-102 (2011) - Wenjun Zhou, Hui Xiong:
Checkpoint evolution for volatile correlation computing. Machine Learning 83(1): 103-131 (2011) - Hendrik Blockeel, Karsten M. Borgwardt, Luc De Raedt, Pedro M. Domingos, Kristian Kersting, Xifeng Yan:
Guest editorial to the special issue on inductive logic programming, mining and learning in graphs and statistical relational learning. Machine Learning 83(2): 133-135 (2011) - Leander Schietgat, Fabrizio Costa, Jan Ramon, Luc De Raedt:
Effective feature construction by maximum common subgraph sampling. Machine Learning 83(2): 137-161 (2011) - Ondrej Kuzelka, Filip Zelezný:
Block-wise construction of tree-like relational features with monotone reducibility and redundancy. Machine Learning 83(2): 163-192 (2011) - Andreas Maunz, Christoph Helma, Stefan Kramer:
Efficient mining for structurally diverse subgraph patterns in large molecular databases. Machine Learning 83(2): 193-218 (2011) - Marco Lippi, Manfred Jaeger, Paolo Frasconi, Andrea Passerini:
Relational information gain. Machine Learning 83(2): 219-239 (2011) - Taisuke Sato, Masakazu Ishihata, Katsumi Inoue:
Constraint-based probabilistic modeling for statistical abduction. Machine Learning 83(2): 241-264 (2011) - Justin Guinney, Qiang Wu, Sayan Mukherjee:
Estimating variable structure and dependence in multitask learning via gradients. Machine Learning 83(3): 265-287 (2011) - Steffen Grünewälder, Klaus Obermayer:
The optimal unbiased value estimator and its relation to LSTD, TD and MC. Machine Learning 83(3): 289-330 (2011) - David R. Hardoon, John Shawe-Taylor:
Sparse canonical correlation analysis. Machine Learning 83(3): 331-353 (2011) - Marco Grzegorczyk, Dirk Husmeier:
Non-homogeneous dynamic Bayesian networks for continuous data. Machine Learning 83(3): 355-419 (2011) - Shimon Whiteson, Michael L. Littman:
Introduction to the special issue on empirical evaluations in reinforcement learning. Machine Learning 84(1-2): 1-6 (2011) - Tim Kovacs, Robert Egginton:
On the analysis and design of software for reinforcement learning, with a survey of existing systems. Machine Learning 84(1-2): 7-49 (2011) - Peter Vamplew, Richard Dazeley, Adam Berry, Rustam Issabekov, Evan Dekker:
Empirical evaluation methods for multiobjective reinforcement learning algorithms. Machine Learning 84(1-2): 51-80 (2011) - Alan Fern, Roni Khardon, Prasad Tadepalli:
The first learning track of the international planning competition. Machine Learning 84(1-2): 81-107 (2011) - Susan M. Shortreed, Eric B. Laber, Daniel J. Lizotte, T. Scott Stroup, Joelle Pineau, Susan A. Murphy:
Informing sequential clinical decision-making through reinforcement learning: an empirical study. Machine Learning 84(1-2): 109-136 (2011) - Roland Hafner, Martin A. Riedmiller:
Reinforcement learning in feedback control - Challenges and benchmarks from technical process control. Machine Learning 84(1-2): 137-169 (2011) - Jens Kober, Jan Peters:
Policy search for motor primitives in robotics. Machine Learning 84(1-2): 171-203 (2011) - Shivaram Kalyanakrishnan, Peter Stone:
Characterizing reinforcement learning methods through parameterized learning problems. Machine Learning 84(1-2): 205-247 (2011) - Chris D. Bartels, Jeff A. Bilmes:
Creating non-minimal triangulations for use in inference in mixed stochastic/deterministic graphical models. Machine Learning 84(3): 249-289 (2011) - Sanjay Jain, Efim B. Kinber:
Iterative learning from texts and counterexamples using additional information. Machine Learning 84(3): 291-333 (2011) - Amy McGovern, Kiri L. Wagstaff:
Machine learning in space: extending our reach. Machine Learning 84(3): 335-340 (2011) - Michael C. Burl, Philipp Georg Wetzler:
Onboard object recognition for planetary exploration. Machine Learning 84(3): 341-367 (2011) - Süreyya Özögür-Akyüz, Devrim Ünay, Alexander J. Smola:
Guest editorial: model selection and optimization in machine learning. Machine Learning 85(1-2): 1-2 (2011) - Bharath K. Sriperumbudur, David A. Torres, Gert R. G. Lanckriet:
A majorization-minimization approach to the sparse generalized eigenvalue problem. Machine Learning 85(1-2): 3-39 (2011) - Hsiang-Fu Yu, Fang-Lan Huang, Chih-Jen Lin:
Dual coordinate descent methods for logistic regression and maximum entropy models. Machine Learning 85(1-2): 41-75 (2011) - Taiji Suzuki, Ryota Tomioka:
SpicyMKL: a fast algorithm for Multiple Kernel Learning with thousands of kernels. Machine Learning 85(1-2): 77-108 (2011) - Peter Karsmakers, Kristiaan Pelckmans, Kris De Brabanter, Hugo Van hamme, Johan A. K. Suykens:
Sparse conjugate directions pursuit with application to fixed-size kernel models. Machine Learning 85(1-2): 109-148 (2011) - Olivier Chapelle, Pannagadatta K. Shivaswamy, Srinivas Vadrevu, Kilian Q. Weinberger, Ya Zhang, Belle L. Tseng:
Boosted multi-task learning. Machine Learning 85(1-2): 149-173 (2011) - Gregory M. Moore, Charles Bergeron, Kristin P. Bennett:
Model selection for primal SVM. Machine Learning 85(1-2): 175-208 (2011) - Zeev Volkovich, Zeev Barzily, Gerhard-Wilhelm Weber, Dvora Toledano-Kitai, Renata Avros:
Resampling approach for cluster model selection. Machine Learning 85(1-2): 209-248 (2011) - Takashi Takenouchi, Shin Ishii:
Ternary Bradley-Terry model-based decoding for multi-class classification and its extensions. Machine Learning 85(3): 249-272 (2011) - Marta Arias, José L. Balcázar:
Construction and learnability of canonical Horn formulas. Machine Learning 85(3): 273-297 (2011) - Amir Massoud Farahmand, Csaba Szepesvári:
Model selection in reinforcement learning. Machine Learning 85(3): 299-332 (2011) - Jesse Read, Bernhard Pfahringer, Geoff Holmes, Eibe Frank:
Classifier chains for multi-label classification. Machine Learning 85(3): 333-359 (2011) - Junya Honda, Akimichi Takemura:
An asymptotically optimal policy for finite support models in the multiarmed bandit problem. Machine Learning 85(3): 361-391 (2011) - Shumei Zhang, Paul J. McCullagh, Chris D. Nugent, Huiru Zheng, Matthias Baumgarten:
Optimal model selection for posture recognition in home-based healthcare. Int. J. Machine Learning & Cybernetics 2(1): 1-14 (2011) - Yi Tang, Pingkun Yan, Yuan Yuan, Xuelong Li:
Single-image super-resolution via local learning. Int. J. Machine Learning & Cybernetics 2(1): 15-23 (2011) - Li-Juan Wang:
An improved multiple fuzzy NNC system based on mutual information and fuzzy integral. Int. J. Machine Learning & Cybernetics 2(1): 25-36 (2011) - Zhi Liu, Qihang Wu, Yun Zhang, C. L. Philip Chen:
Adaptive least squares support vector machines filter for hand tremor canceling in microsurgery. Int. J. Machine Learning & Cybernetics 2(1): 37-47 (2011) - Qiang He, Congxin Wu:
Separating theorem of samples in Banach space for support vector machine learning. Int. J. Machine Learning & Cybernetics 2(1): 49-54 (2011) - Jie Zhu, Xiaoping Li, Weiming Shen:
Effective genetic algorithm for resource-constrained project scheduling with limited preemptions. Int. J. Machine Learning & Cybernetics 2(2): 55-65 (2011) - Weiguo Yi, Mingyu Lu, Zhi Liu:
Multi-valued attribute and multi-labeled data decision tree algorithm. Int. J. Machine Learning & Cybernetics 2(2): 67-74 (2011) - Alfons Schuster, Yoko Yamaguchi:
From foundational issues in artificial intelligence to intelligent memristive nano-devices. Int. J. Machine Learning & Cybernetics 2(2): 75-87 (2011) - Jie Li, Guan Han, Jing Wen, Xinbo Gao:
Robust tensor subspace learning for anomaly detection. Int. J. Machine Learning & Cybernetics 2(2): 89-98 (2011) - G. S. Mahapatra, T. K. Mandal, G. P. Samanta:
A production inventory model with fuzzy coefficients using parametric geometric programming approach. Int. J. Machine Learning & Cybernetics 2(2): 99-105 (2011) - Guang-Bin Huang, Dianhui Wang, Yuan Lan:
Extreme learning machines: a survey. Int. J. Machine Learning & Cybernetics 2(2): 107-122 (2011) - Grigori Sidorov, Mario Koeppen, Nareli Cruz Cortés:
Editorial. Int. J. Machine Learning & Cybernetics 2(3): 123-124 (2011) - Omer Boehm, David R. Hardoon, Larry M. Manevitz:
Classifying cognitive states of brain activity via one-class neural networks with feature selection by genetic algorithms. Int. J. Machine Learning & Cybernetics 2(3): 125-134 (2011) - Vadim N. Vagin, Marina V. Fomina:
Problem of knowledge discovery in noisy databases. Int. J. Machine Learning & Cybernetics 2(3): 135-145 (2011) - Antonio Camarena-Ibarrola, Edgar Chávez:
Online music tracking with global alignment. Int. J. Machine Learning & Cybernetics 2(3): 147-156 (2011) - Boris Stilman, Vladimir Yakhnis, Oleg Umanskiy:
The Primary Language of ancient battles. Int. J. Machine Learning & Cybernetics 2(3): 157-176 (2011) - Julio Javier Castillo:
A WordNet-based semantic approach to textual entailment and cross-lingual textual entailment. Int. J. Machine Learning & Cybernetics 2(3): 177-189 (2011) - Songfeng Zheng:
Gradient descent algorithms for quantile regression with smooth approximation. Int. J. Machine Learning & Cybernetics 2(3): 191-207 (2011) - Herón Molina-Lozano:
A new fast fuzzy Cocke-Younger-Kasami algorithm for DNA strings analysis. Int. J. Machine Learning & Cybernetics 2(3): 209-218 (2011) - Hardik N. Soni, Nita H. Shah:
Optimal policy for fuzzy expected value production inventory model with imprecise production preparation-time. Int. J. Machine Learning & Cybernetics 2(4): 219-224 (2011) - Chih-Min Lin, Ming-Chia Li, Ang-Bung Ting, Ming-Hung Lin:
A robust self-learning PID control system design for nonlinear systems using a particle swarm optimization algorithm. Int. J. Machine Learning & Cybernetics 2(4): 225-234 (2011) - Lin Yao, Chengjie Sun, Yan Wu, Xiaolong Wang, Xuan Wang:
Biomedical named entity recognition using generalized expectation criteria. Int. J. Machine Learning & Cybernetics 2(4): 235-243 (2011) - Bruce Poon, M. Ashraful Amin, Hong Yan:
Performance evaluation and comparison of PCA Based human face recognition methods for distorted images. Int. J. Machine Learning & Cybernetics 2(4): 245-259 (2011) - Jun Wu, Shitong Wang, Fu-Lai Chung:
Positive and negative fuzzy rule system, extreme learning machine and image classification. Int. J. Machine Learning & Cybernetics 2(4): 261-271 (2011) - William Zhu, Shiping Wang:
Matroidal approaches to generalized rough sets based on relations. Int. J. Machine Learning & Cybernetics 2(4): 273-279 (2011) - Duo Pei, Ju-Sheng Mi:
Attribute reduction in decision formal context based on homomorphism. Int. J. Machine Learning & Cybernetics 2(4): 289-293 (2011) - Panagis Magdalinos, Apostolos Kousaridas, Panagiotis Spapis, George Katsikas, Nancy Alonistioti:
Enhancing a Fuzzy Logic Inference Engine through Machine Learning for a Self- Managed Network. MONET 16(4): 475-489 (2011) - Bipin K. Tripathi, Prem K. Kalra:
On the learning machine for three dimensional mapping. Neural Computing and Applications 20(1): 105-111 (2011) - Carmen Vidaurre, Claudia Sannelli, Klaus-Robert Müller, Benjamin Blankertz:
Machine-Learning-Based Coadaptive Calibration for Brain-Computer Interfaces. Neural Computation 23(3): 791-816 (2011) - Steven Lemm, Benjamin Blankertz, Thorsten Dickhaus, Klaus-Robert Müller:
Introduction to machine learning for brain imaging. NeuroImage 56(2): 387-399 (2011) - Ariana Anderson, Jennifer S. Labus, Eduardo P. Vianna, Emeran A. Mayer, Mark S. Cohen:
Common component classification: What can we learn from machine learning? NeuroImage 56(2): 517-524 (2011) - Pamela K. Douglas, Sam Harris, Alan L. Yuille, Mark S. Cohen:
Performance comparison of machine learning algorithms and number of independent components used in fMRI decoding of belief vs. disbelief. NeuroImage 56(2): 544-553 (2011) - Angela Rizk-Jackson, Diederick Stoffers, Sarah Sheldon, Joshua M. Kuperman, Anders M. Dale, Jody Goldstein, Jody Corey-Bloom, Russell A. Poldrack, Adam R. Aron:
Evaluating imaging biomarkers for neurodegeneration in pre-symptomatic Huntington's disease using machine learning techniques. NeuroImage 56(2): 788-796 (2011) - Ilia Nouretdinov, Sergi G. Costafreda, Alexander Gammerman, Alexey Ya. Chervonenkis, Vladimir Vovk, Vladimir Vapnik, Cynthia H. Y. Fu:
Machine learning classification with confidence: Application of transductive conformal predictors to MRI-based diagnostic and prognostic markers in depression. NeuroImage 56(2): 809-813 (2011) - Oscar Cordón, Przemyslaw Kazienko, Bogdan Trawinski:
Special Issue on Hybrid and Ensemble Methods in Machine Learning. New Generation Comput. 29(3): 241-244 (2011) - Christof Monz:
Machine learning for query formulation in question answering. Natural Language Engineering 17(4): 425-454 (2011) - Jiuwen Cao, Zhiping Lin, Guang-Bin Huang:
Composite Function Wavelet Neural Networks with Differential Evolution and Extreme Learning Machine. Neural Processing Letters 33(3): 251-265 (2011) - Kamlesh Dutta, Saroj Kaushik, Nupur Prakash:
Machine Learning Approach for the Classification of Demonstrative Pronouns for Indirect Anaphora in Hindi News Items. Prague Bull. Math. Linguistics 95: 33-50 (2011) - Rubén Izquierdo:
An Approach to Word Sense Disambiguation based on Semantic Classes and Machine Learning. Procesamiento del Lenguaje Natural 46: 123-124 (2011) - Yi Zhang, Marija D. Ilic, Ozan K. Tonguz:
Mitigating Blackouts via Smart Relays: A Machine Learning Approach. Proceedings of the IEEE 99(1): 94-118 (2011) - Abdul Adeel Mohammed, Rashid Minhas, Q. M. Jonathan Wu, Maher A. Sid-Ahmed:
Human face recognition based on multidimensional PCA and extreme learning machine. Pattern Recognition 44(10-11): 2588-2597 (2011) - Richard H. Byrd, Gillian M. Chin, Will Neveitt, Jorge Nocedal:
On the Use of Stochastic Hessian Information in Optimization Methods for Machine Learning. SIAM Journal on Optimization 21(3): 977-995 (2011) - Peter Bodík:
Overview of the workshop on managing large-scale systems via the analysis of system logs and the application of machine learning techniques. Operating Systems Review 45(3): 20-22 (2011) - Terry Ngo:
Data mining: practical machine learning tools and technique, third edition by Ian H. Witten, Eibe Frank, Mark A. Hell. ACM SIGSOFT Software Engineering Notes 36(5): 51-52 (2011) - Marenglen Biba, Fatos Xhafa, Floriana Esposito, Stefano Ferilli:
Stochastic simulation and modelling of metabolic networks in a machine learning framework. Simulation Modelling Practice and Theory 19(9): 1957-1966 (2011) - Xiao-Lei Xia, Kang Li, George W. Irwin:
A hierarchical multiclass support vector machine incorporated with holistic triple learning units. Soft Comput. 15(5): 833-843 (2011) - Witold Pedrycz, Daniel S. Yeung, Xizhao Wang:
Recent advances on machine learning and Cybernetics. Soft Comput. 15(6): 1039 (2011) - Yacine Laalaoui, Habiba Drias:
Learning and backtracking in non-preemptive scheduling of tasks under timing constraints - Special issue on machine learning and cybernetics. Soft Comput. 15(6): 1071-1086 (2011) - Paul C. Conilione, Dianhui Wang:
Automatic localization and annotation of facial features using machine learning techniques. Soft Comput. 15(6): 1231-1245 (2011) - Hisao Ishibuchi, Yusuke Nakashima, Yusuke Nojima:
Performance evaluation of evolutionary multiobjective optimization algorithms for multiobjective fuzzy genetics-based machine learning. Soft Comput. 15(12): 2415-2434 (2011) - Paul Honeine, Cédric Richard:
Preimage Problem in Kernel-Based Machine Learning. IEEE Signal Process. Mag. 28(2): 77-88 (2011) - Xiaodong He, Li Deng:
Speech Recognition, Machine Translation, and Speech Translation - A Unified Discriminative Learning Paradigm [Lecture Notes]. IEEE Signal Process. Mag. 28(5): 126-133 (2011) - Tülay Adali, David J. Miller, Konstantinos I. Diamantaras, Jan Larsen:
Trends in Machine Learning for Signal Processing [In the Spotlight]. IEEE Signal Process. Mag. 28(6): 193-196 (2011) - Bo Liu, Dixian Zhao, Patrick Reynaert, Georges G. E. Gielen:
Synthesis of Integrated Passive Components for High-Frequency RF ICs Based on Evolutionary Computation and Machine Learning Techniques. IEEE Trans. on CAD of Integrated Circuits and Systems 30(10): 1458-1468 (2011) - Duo Ding, J. Andres Torres, David Z. Pan:
High Performance Lithography Hotspot Detection With Successively Refined Pattern Identifications and Machine Learning. IEEE Trans. on CAD of Integrated Circuits and Systems 30(11): 1621-1634 (2011) - Qiwen Dong, Shuigeng Zhou:
Novel Nonlinear Knowledge-Based Mean Force Potentials Based on Machine Learning. IEEE/ACM Trans. Comput. Biology Bioinform. 8(2): 476-486 (2011) - Aditya Kumar Sehgal, Sanmay Das, Keith Noto, Milton H. Saier Jr., Charles Elkan:
Identifying Relevant Data for a Biological Database: Handcrafted Rules versus Machine Learning. IEEE/ACM Trans. Comput. Biology Bioinform. 8(3): 851-857 (2011) - Aris Gkoulalas-Divanis, Yücel Saygin, Vassilios S. Verykios:
Foreword for the special issue of selected papers from the 1st ECML/PKDD Workshop on Privacy and Security issues in Data Mining and Machine Learning. Transactions on Data Privacy 4(3): 127-128 (2011) - Giovanni Acampora, José Manuel Cadenas, Vincenzo Loia, Enrique Muñoz Ballester:
Achieving Memetic Adaptability by Means of Agent-Based Machine Learning. IEEE Trans. Industrial Informatics 7(4): 557-569 (2011) - Guang Xiang, Jason I. Hong, Carolyn Penstein Rosé, Lorrie Faith Cranor:
CANTINA+: A Feature-Rich Machine Learning Framework for Detecting Phishing Web Sites. ACM Trans. Inf. Syst. Secur. 14(2): 21 (2011) - Charles X. Ling:
Introduction to special issue on machine learning for business applications. ACM TIST 2(3): 18 (2011) - Chun-Nan Hsu:
Introduction to special issue on large-scale machine learning. ACM TIST 2(3): 25 (2011) - Vikraman Baskaran, Aziz Guergachi, Rajeev K. Bali, Raouf N. Gorgui-Naguib:
Predicting Breast Screening Attendance Using Machine Learning Techniques. IEEE Transactions on Information Technology in Biomedicine 15(2): 251-259 (2011) - Oana Frunza, Diana Inkpen, Thomas Tran:
A Machine Learning Approach for Identifying Disease-Treatment Relations in Short Texts. IEEE Trans. Knowl. Data Eng. 23(6): 801-814 (2011) - Emilio Soria-Olivas, Juan Gómez-Sanchís, José David Martín-Guerrero, Joan Vila-Francés, Marcelino Martínez-Sober, José Rafael Magdalena Benedito, Antonio J. Serrano:
BELM: Bayesian Extreme Learning Machine. IEEE Transactions on Neural Networks 22(3): 505-509 (2011) - Bipin Kumar Tripathi, Prem Kumar Kalra:
On Efficient Learning Machine With Root-Power Mean Neuron in Complex Domain. IEEE Transactions on Neural Networks 22(5): 727-738 (2011) - Oliver Lemon, Olivier Pietquin:
Introduction to special issue on machine learning for adaptivity in spoken dialogue systems. TSLP 7(3): 3 (2011) - Karthik Nagarajan, Brian Holland, Alan D. George, K. Clint Slatton, Herman Lam:
Accelerating Machine-Learning Algorithms on FPGAs using Pattern-Based Decomposition. Signal Processing Systems 62(1): 43-63 (2011) - Jocelyn Chanussot, Christian Jutten:
Special Issue on Machine Learning for Signal Processing. Signal Processing Systems 65(3): 287-288 (2011) - Eyke Hüllermeier:
Fuzzy machine learning and data mining. Wiley Interdisc. Rew.: Data Mining and Knowledge Discovery 1(4): 269-283 (2011) - Satoru Ohta, Takehito Hirota:
Machine Learning Approach to the Power Management of Server Clusters. CIT 2011: 571-578 - Yingxu Wang, Yousheng Tian, Kendall Hu:
The operational semantics of Concept Algebra for cognitive computing and machine learning. IEEE ICCI*CC 2011: 49-58 - Saleema Amershi, James Fogarty, Ashish Kapoor, Desney S. Tan:
Effective End-User Interaction with Machine Learning. AAAI 2011 - Nikolaos Tziortziotis, Konstantinos Blekas:
A Bayesian Reinforcement Learning framework Using Relevant Vector Machines. AAAI 2011 - Avneet Kaur Dhawan, Jaswinder Singh:
Modeling and designing of machine learning procedures as applied to game playing using artificial intelligence. ACAI 2011: 139-143 - Kuldeep Singh, S. Agrawal:
Feature extraction based IP traffic classification using machine learning. ACAI 2011: 208-212 - Jyoti Grover, Nitesh Kumar Prajapati, Vijay Laxmi, Manoj Singh Gaur:
Machine Learning Approach for Multiple Misbehavior Detection in VANET. ACC (3) 2011: 644-653 - Mohammed E. Hoque, Daniel McDuff, Louis-Philippe Morency, Rosalind W. Picard:
Machine Learning for Affective Computing. ACII (2) 2011: 567 - Yunqiang Liu, Vicent Caselles:
Improved Support Vector Machines with Distance Metric Learning. ACIVS 2011: 82-91 - Daniel Ortiz-Martínez, Luis A. Leiva, Vicent Alabau, Ismael García-Varea, Francisco Casacuberta:
An Interactive Machine Translation System with Online Learning. ACL (System Demonstrations) 2011: 68-73 - Bing Zhao, Young-Suk Lee, Xiaoqiang Luo, Liu Li:
Learning to Transform and Select Elementary Trees for Improved Syntax-based Machine Translations. ACL 2011: 846-855 - Phil Schniter:
Session TP8b1: Machine-learning-based statistical signal processing. ACSCC 2011: 1874-1876 - Daniel L. Silver:
Machine Lifelong Learning: Challenges and Benefits for Artificial General Intelligence. AGI 2011: 370-375 - Junjie Zou, Zhengtao Yu, Huanyun Zong, Xing Zhao:
Active Learning for Sparse Least Squares Support Vector Machines. AICI (2) 2011: 672-679 - Fernando García-García, Gema García-Sáez, Paloma Chausa, Iñaki Martínez-Sarriegui, Pedro José Benito, Enrique J. Gómez, M. Elena Hernando:
Statistical Machine Learning for Automatic Assessment of Physical Activity Intensity Using Multi-axial Accelerometry and Heart Rate. AIME 2011: 70-79 - Aydano P. Machado, João Marcelo Lyra, Renato Ambrósio Jr., Guilherme Ribeiro, Luana P. N. Araújo, Camilla Xavier, Evandro Costa:
Comparing Machine-Learning Classifiers in Keratoconus Diagnosis from ORA Examinations. AIME 2011: 90-95 - Rui Zhang, Yuan Lan, Guang-Bin Huang, Yeng Chai Soh:
Extreme Learning Machine with Adaptive Growth of Hidden Nodes and Incremental Updating of Output Weights. AIS 2011: 253-262 - Weiwei Zong, Hongming Zhou, Guang-Bin Huang, Zhiping Lin:
Face Recognition Based on Kernelized Extreme Learning Machine. AIS 2011: 263-272 - Stuart Harvey Rubin, Gordon K. Lee:
Human-Machine Learning for Intelligent Aircraft Systems. AIS 2011: 331-342 - Theja Tulabandhula, Cynthia Rudin, Patrick Jaillet:
The Machine Learning and Traveling Repairman Problem. ADT 2011: 262-276 - Aditya V. Nori, Sriram K. Rajamani:
Program Analysis and Machine Learning: A Win-Win Deal. APLAS 2011: 1-2 - Duo Ding, Andres J. Torres, Fedor G. Pikus, David Z. Pan:
High performance lithographic hotspot detection using hierarchically refined machine learning. ASP-DAC 2011: 775-780 - Xia Ning, Michael A. Walters, George Karypis:
Improved machine learning models for predicting selective compounds. BCB 2011: 106-115 - Sabareesh Subramaniam, Sriraam Natarajan, Alessandro Senes:
A machine learning based approach to improve sidechain optimization. BCB 2011: 478-480 - Ali Mahmood Khan:
Personal state and emotion monitoring by wearable computing and machine learning. BCS HCI 2011: 543-545 - (Zhou) Bryan Bai, Stefan C. Kremer:
Regularization of sequence data for machine learning. BIBM Workshops 2011: 19-25 - Utku Erdogdu, Mehmet Tan, Reda Alhajj, Faruk Polat, Douglas J. Demetrick, Jon G. Rokne:
Employing Machine Learning Techniques for Data Enrichment: Increasing the Number of Samples for Effective Gene Expression Data Analysis. BIBM 2011: 238-242 - Masood Zamani, Stefan C. Kremer:
Amino acid encoding schemes for machine learning methods. BIBM Workshops 2011: 327-333 - Hossam M. Ashtawy, Nihar R. Mahapatra:
A Comparative Assessment of Conventional and Machine-Learning-Based Scoring Functions in Predicting Binding Affinities of Protein-Ligand Complexes. BIBM 2011: 627-630 - Prabha Garg, Anju Sharma, Rajender Kumar, Pawan Gupta, Nilanjan Roy:
MSubCellProt: Predicting Protein Multiple Subcellular Localization using Machine Learning. BICoB 2011: 86-91 - Zeehasham Rasheed, Huzefa Rangwala:
TAC-ELM: Metagenomic Taxonomic Classification with Extreme Learning Machines. BICoB 2011: 92-97 - Monther Alhamdoosh, Castrense Savojardo, Piero Fariselli, Rita Casadio:
Disulfide Connectivity Prediction with Extreme Learning Machines. BIOINFORMATICS 2011: 5-14 - Na'el Abu-halaweh, Amit Sabnis, Robert W. Harrison:
Prediction of Regulatory sRNAs in Prokaryotes using Machine Learning Tools. BIOINFORMATICS 2011: 75-81 - Arushi Raghuvanshi, Marek A. Perkowski:
Image Processing and Machine Learning for the Diagnosis of Melanoma Cancer. BIODEVICES 2011: 405-410 - Wencai Zeng, Jiong Jia, Zhonglong Zheng, Chenmao Xie, Li Guo:
A comparison study: Support vector machines for binary classification in machine learning. BMEI 2011: 1621-1625 - Shivakumar Vaithyanathan:
The Power of Declarative Languages: From Information Extraction to Machine Learning. BTW 2011: 23 - Djallel Bouneffouf:
Applying Machine Learning Techniques to Improve User Acceptance on Ubiquitous Environment. CAiSE (Doctoral Consortium) 2011: 3-14 - Mohammed Talat Khouj, Cesar Lopez, Sarbjit Sarkaria, José R. Martí:
Disaster management in real time simulation using machine learning. CCECE 2011: 1507-1510 - Anis Yazidi, Ole-Christoffer Granmo, B. John Oommen:
On the analysis of a new Markov chain which has applications in AI and machine learning. CCECE 2011: 1553-1558 - Ling Huang, Anthony D. Joseph, Blaine Nelson, Benjamin I. P. Rubinstein, J. D. Tygar:
Adversarial machine learning. AISec 2011: 43-58 - Davide Ariu, Giorgio Giacinto, Fabio Roli:
Machine learning in computer forensics (and the lessons learned from machine learning in computer security). AISec 2011: 99-104 - Roland Tóth, Vincent Laurain, Wei Xing Zheng, Kameshwar Poolla:
Model structure learning: A support vector machine approach for LPV linear-regression models. CDC-ECE 2011: 3192-3197 - Danielle N. G. Silva, Luciano D. S. Pacifico, Teresa Bernarda Ludermir:
An evolutionary extreme learning machine based on group search optimization. IEEE Congress on Evolutionary Computation 2011: 574-580 - Riyad Alshammari, A. Nur Zincir-Heywood:
Is machine learning losing the battle to produce transportable signatures against VoIP traffic? IEEE Congress on Evolutionary Computation 2011: 1543-1550 - Meng-Day (Mandel) Yu, David M'Raïhi, Richard Sowell, Srinivas Devadas:
Lightweight and Secure PUF Key Storage Using Limits of Machine Learning. CHES 2011: 358-373 - Duen Horng Chau, Aniket Kittur, Jason I. Hong, Christos Faloutsos:
Apolo: making sense of large network data by combining rich user interaction and machine learning. CHI 2011: 167-176 - Edward W. Lowe, Mariusz Butkiewicz, Matthew Spellings, Albert Omlor, Jens Meiler:
Comparative analysis of machine learning techniques for the prediction of logP. CIBCB 2011: 35-40 - Hercules Dalianis, Jonas Sjöbergh, Eriks Sneiders:
Comparing Manual Text Patterns and Machine Learning for Classification of E-Mails for Automatic Answering by a Government Agency. CICLing (2) 2011: 234-243 - Dimitrios Giannakis, Andrew J. Majda:
Time Series Reconstruction via Machine Learning: Revealing Decadal Variability and Intermittency in the North Pacific Sector of a Coupled Climate Model. CIDU 2011: 107-117 - Laurent El Ghaoui, Guan-Cheng Li, Viet-An Duong, Vu Pham, Ashok N. Srivastava, Kanishka Bhaduri:
Sparse Machine Learning Methods for Understanding Large Text Corpora. CIDU 2011: 159-173 - Ganeshchandra Mallya, Shivam Tripathi, Rao S. Govindaraju:
A Machine Learning Approach for Probabilistic Drough Classification. CIDU 2011: 263-275 - Greg Ashe, Nathan R. Sturtevant, Jong-Hwan Kim:
Keynotes: Data mining and machine learning applications in MMOs. CIG 2011 - Luca Galli, Daniele Loiacono, Luigi Cardamone, Pier Luca Lanzi:
A cheating detection framework for Unreal Tournament III: A machine learning approach. CIG 2011: 266-272 - Ya-nan Qian, Yunhua Hu, Jianling Cui, Qinghua Zheng, Zaiqing Nie:
Combining machine learning and human judgment in author disambiguation. CIKM 2011: 1241-1246 - Tae Rim Lee, Bon Min Goo, Hun Kim, Sang Uk Shin:
Efficient e-Discovery Process Utilizing Combination Method of Machine Learning Algorithms. CIS 2011: 1109-1113 - Daniel J. Arndt, A. Nur Zincir-Heywood:
A Comparison of three machine learning techniques for encrypted network traffic analysis. CISDA 2011: 107-114 - Marenglen Biba, Fatos Xhafa, Floriana Esposito, Stefano Ferilli:
Using Machine Learning Techniques for Modelling and Simulation of Metabolic Networks. CISIS 2011: 85-92 - Cristian-Alexandru Dragusanu, Marina Cufliuc, Adrian Iftene:
Detecting Wikipedia Vandalism using Machine Learning - Notebook for PAN at CLEF 2011. CLEF (Notebook Papers/Labs/Workshop) 2011 - Hiroshi Tamano, Shinji Nakadai, Takuya Araki:
Optimizing Multiple Machine Learning Jobs on MapReduce. CloudCom 2011: 59-66 - Sheng Yu, Yinfeng Xu, Ming Liu, Feifeng Zheng:
Optimal Policy for Single-Machine Scheduling with Deterioration Effects, Learning Effects, Setup Times, and Availability Constraints. COCOA 2011: 64-73 - Ranga Raju Vatsavai, Eddie A. Bright, Varun Chandola, Budhendra L. Bhaduri, Anil Cheriyadat, Jordan Graesser:
Machine learning approaches for high-resolution urban land cover classification: a comparative study. COM.Geo 2011: 11:1-11:10 - Xiulei Qin, Wenbo Zhang, Wei Wang, Jun Wei, Hua Zhong, Tao Huang:
On-line Cache Strategy Reconfiguration for Elastic Caching Platform: A Machine Learning Approach. COMPSAC 2011: 523-534 - Yaqin Yang, Nianwen Xue, Peter Anick:
A Machine Learning-Based Coreference Detection System for OntoNotes. CoNLL Shared Task 2011: 117-121 - Yu Wang, Yang Xiang, Shunzheng Yu:
Internet Traffic Classification Using Machine Learning: A Token-based Approach. CSE 2011: 285-289 - Stéphane Ross, Daniel Munoz, Martial Hebert, J. Andrew Bagnell:
Learning message-passing inference machines for structured prediction. CVPR 2011: 2737-2744 - Jue Xie, Frada Burstein:
Using Machine Learning to Support Resource Quality Assessment: An Adaptive Attribute-Based Approach for Health Information Portals. DASFAA Workshops 2011: 526-537 - Sébastien Darfeuille, Christophe Kelma:
Production test of an RF receiver chain based on ATM combining RF BIST and machine learning algorithm. ECCTD 2011: 653-656 - David Leonard, David Lillis, Lusheng Zhang, Fergus Toolan, Rem W. Collier, John Dunnion:
Applying Machine Learning Diversity Metrics to Data Fusion in Information Retrieval. ECIR 2011: 695-698 - Nan Li, William W. Cohen, Kenneth R. Koedinger, Noboru Matsuda:
A Machine Learning Approach for Automatic Student Model Discovery. EDM 2011: 31-40 - Yi Lin, Yue Liu:
Research on Recognition and Mobile Learning of Birds Base on Network under the Condition of Human-Machine Collaboration. Edutainment 2011: 115-122 - Wen Zhang, Ye Yang, Qing Wang:
On the Predictability of Software Efforts using Machine Learning Techniques. ENASE 2011: 5-14 - Alfredo Vellido, José D. Martín, Fabrice Rossi, Paulo J. G. Lisboa:
Seeing is believing: The importance of visualization in real-world machine learning applications. ESANN 2011 - Carina Walter, Gabriele Cierniak, Peter Gerjets, Wolfgang Rosenstiel, Martin Bogdan:
Classifying mental states with machine learning algorithms using alpha activity decline. ESANN 2011 - Johannes Borgström, Andrew D. Gordon, Michael Greenberg, James Margetson, Jurgen Van Gael:
Measure Transformer Semantics for Bayesian Machine Learning. ESOP 2011: 77-96 - Veli Bicer, Thanh Tran, Anna Gossen:
Relational Kernel Machines for Learning from Graph-Structured RDF Data. ESWC (1) 2011: 47-62 - Carlo Allocca:
Automatic Identification of Ontology Versions Using Machine Learning Techniques. ESWC (1) 2011: 352-366 - Maya Kallas, Paul Honeine, Cédric Richard, Clovis Francis, Hassan Amoud:
Non-negative pre-image in machine learning for pattern recognition. EUSIPCO 2011: 931-935 - Sara Silva, Orlando Anunciação, Marco Lotz:
A Comparison of Machine Learning Methods for the Prediction of Breast Cancer. EvoBio 2011: 159-170 - Hossam M. Zawbaa, Nashwa El-Bendary, Aboul Ella Hassanien, Tai-Hoon Kim:
Machine Learning-Based Soccer Video Summarization System. FGIT-MulGraB (2) 2011: 19-28 - Mario Rojas Quiñones, David Masip, Jordi Vitrià:
Predicting dominance judgements automatically: A machine learning approach. FG 2011: 939-944 - Eni Mustafaraj, Scott D. Anderson:
Learning about Machine Learning: An Extended Assignment to Classify Twitter Accounts. FLAIRS Conference 2011 - Travis Rasor, Andrew Olney, Sidney K. D'Mello:
Student Speech Act Classification Using Machine Learning. FLAIRS Conference 2011 - Julio Villena-Román, Sonia Collada-Pérez, Sara Lana-Serrano, José Carlos González Cristóbal:
Hybrid Approach Combining Machine Learning and a Rule-Based Expert System for Text Categorization. FLAIRS Conference 2011 - Amel Bennaceur, Valérie Issarny, Richard Johansson, Alessandro Moschitti, Romina Spalazzese, Daniel Sykes:
Automatic Service Categorisation through Machine Learning in Emergent Middleware. FMCO 2011: 133-149 - Enrico Ferrari, Marco Muselli:
Implementing reliable learning through Reliable Support Vector Machines. FOCI 2011: 100-106 - Zhenlong Sun, Conghui Zhu, Bing Xu, Sheng Li:
Research on machine learning method-based combination forecasting model and its application. FSKD 2011: 1226-1231 - Tienan Feng, Dingli Jin, Liang Da, Yifei Wang:
The local protein-protein interactional feature can be caught by machine-learning method. FSKD 2011: 1633-1637 - Filippo Caschera, Martin M. Hanczyc, Steen Rasmussen:
Machine learning for drug design, molecular machines and evolvable artificial cells. GECCO (Companion) 2011: 831-832 - Jaume Bacardit, Xavier Llorà:
Large scale data mining using genetics-based machine learning. GECCO (Companion) 2011: 1285-1310 - Bruno Martins:
A Supervised Machine Learning Approach for Duplicate Detection over Gazetteer Records. GeoS 2011: 34-51 - Leone Pereira Masiero, Marco Antonio Casanova, Marcelo Tílio Monteiro de Carvalho:
Travel time prediction using machine learning. CTS@GIS 2011: 34-38 - Zrinka Puljiz, Mijung Park, Robert W. Heath Jr.:
A Machine Learning Approach to Link Adaptation for SC-FDE System. GLOBECOM 2011: 1-5 - Josep Lluis Berral, Ricard Gavaldà, Jordi Torres:
Adaptive Scheduling on Power-Aware Managed Data-Centers Using Machine Learning. GRID 2011: 66-73 - Anis Yazidi, Ole-Christoffer Granmo, B. John Oommen:
A New Tool for the Modeling of AI and Machine Learning Applications: Random Walk-Jump Processes. HAIS (1) 2011: 11-21 - Ryan Kirk:
Extracts Cognitive Artifacts from Text through Combining Human and Machine Learning in an Iterative Fashion. HCI (22) 2011: 293-297 - Manisha Pujari, Rushed Kanawati:
A Supervised Machine Learning Link Prediction Approach for Tag Recommendation. HCI (18) 2011: 336-344 - K. Karthik, R. Ponnusamy:
Adaptive Machine Learning Approach for Emotional Email Classification. HCI (3) 2011: 552-558 - Fernando J. López-Colino, Javier Tejedor, Jordi Porta, José Colás:
Integration of a Spanish-to-LSE Machine Translation System into an e-learning Platform. HCI (8) 2011: 567-576 - David Lahoz, Beatriz Lacruz, Pedro M. Mateo:
A bi-objective micro genetic Extreme Learning Machine. HIMA 2011: 68-75 - Márcio Bastos Castro, Luís Fabrício Wanderley Góes, Christiane Pousa Ribeiro, Murray Cole, Marcelo Cintra, Jean-François Méhaut:
A machine learning-based approach for thread mapping on transactional memory applications. HiPC 2011: 1-10 - Elaine Short, David Feil-Seifer, Maja J. Mataric:
A comparison of machine learning techniques for modeling human-robot interaction with children with autism. HRI 2011: 251-252 - Chad M. Cumby, Rayid Ghani:
A Machine Learning Based System for Semi-Automatically Redacting Documents. IAAI 2011 - Nisarg Vyas, Jonathan Farringdon, David Andre, John Ivo Stivoric:
Machine Learning and Sensor Fusion for Estimating Continuous Energy Expenditure. IAAI 2011 - Pascual Martínez-Gómez, Germán Sanchis-Trilles, Francisco Casacuberta:
Passive-Aggressive for On-Line Learning in Statistical Machine Translation. IbPRIA 2011: 240-247 - Timo Reuter, Philipp Cimiano:
Learning Similarity Functions for Event Identification using Support Vector Machines. KDIR 2011: 208-215 - Przemyslaw Klesk:
A Relationship between Cross-validation and Vapnik Bounds on Generalization of Learning Machines. ICAART (1) 2011: 5-17 - Jonathan Eastep, David Wingate, Anant Agarwal:
Smart data structures: an online machine learning approach to multicore data structures. ICAC 2011: 11-20 - Yan Zhang, Guoshao Su, Liubin Yan:
Gaussian Process Machine Learning Model for Forecasting of Karstic Collapse. ICAIC (1) 2011: 365-372 - KyungHyun Cho, Alexander Ilin, Tapani Raiko:
Improved Learning of Gaussian-Bernoulli Restricted Boltzmann Machines. ICANN (1) 2011: 10-17 - Ignacio Díaz Blanco, Abel A. Cuadrado Vega, Alberto B. Diez, Manuel Domínguez-González:
Manifold Learning for Visualization of Vibrational States of a Rotating Machine. ICANN (2) 2011: 285-292 - Klaus Neumann, Jochen J. Steil:
Batch Intrinsic Plasticity for Extreme Learning Machines. ICANN (1) 2011: 339-346 - Jyri Saarikoski, Jorma Laurikkala, Kalervo Järvelin, Martti Juhola:
Self-Organising Maps in Document Classification: A Comparison with Six Machine Learning Methods. ICANNGA (1) 2011: 260-269 - Elena Hensinger, Ilias N. Flaounas, Nello Cristianini:
Learning Readers' News Preferences with Support Vector Machines. ICANNGA (2) 2011: 322-331 - Benjamin Johnen, Carsten Scheele, Bernd Kuhlenkötter:
Learning robot behavior with artificial neural networks and a coordinate measuring machine. ICARA 2011: 208-213 - Kyong-Ho Lee, Sun-Yuan Kung, Naveen Verma:
Improving kernel-energy trade-offs for machine learning in implantable and wearable biomedical applications. ICASSP 2011: 1597-1600 - Satoshi Kon, Toshihisa Tanaka, Humihiko Mizutani, Masakazu Wada:
A machine learning based approach to weather parameter estimation in Doppler weather radar. ICASSP 2011: 2152-2155 - Navdeep Jaitly, Geoffrey E. Hinton:
Learning a better representation of speech soundwaves using restricted boltzmann machines. ICASSP 2011: 5884-5887 - Bruno Astuto A. Nunes, Kerry Veenstra, William Ballenthin, Stephanie M. Lukin, Katia Obraczka:
A Machine Learning Approach to End-to-End RTT Estimation and its Application to TCP. ICCCN 2011: 1-6 - Changshu Zhang, Arun Ravindran, Kushal Datta, Arindam Mukherjee, Bharat Joshi:
A machine learning approach to modeling power and performance of chip multiprocessors. ICCD 2011: 45-50 - Amol Ghoting, Rajasekar Krishnamurthy, Edwin P. D. Pednault, Berthold Reinwald, Vikas Sindhwani, Shirish Tatikonda, Yuanyuan Tian, Shivakumar Vaithyanathan:
SystemML: Declarative machine learning on MapReduce. ICDE 2011: 231-242 - Brett W. Bader, W. Philip Kegelmeyer, Peter A. Chew:
Multilingual Sentiment Analysis Using Latent Semantic Indexing and Machine Learning. ICDM Workshops 2011: 45-52 - Jun Li:
A Study on Noisy Typing Stream Analysis Using Machine Learning Approach. ICEIS 2011: 149-161 - Yibin Ye, Stefano Squartini, Francesco Piazza:
On-Line Extreme Learning Machine for Training Time-Varying Neural Networks. ICIC (3) 2011: 49-54 - Jeen-Shing Wang, Che-Wei Lin, Ya-Ting C. Yang, Tzu-Ping Kao, Wei-Hsin Wang, Yen-Shiun Chen:
A PACE Sensor System with Machine Learning-Based Energy Expenditure Regression Algorithm. ICIC (3) 2011: 529-536 - Fei Han, Hai-Fen Yao, Qing-Hua Ling:
An Improved Extreme Learning Machine Based on Particle Swarm Optimization. ICIC (3) 2011: 699-704 - Ting Wang, Christophe Sabourin, Kurosh Madani:
Strategy based on Machine Learning for the Control of a Rigid Formation in a Multi-robots Frame. ICINCO (2) 2011: 300-303 - Andrea Schirru, Simone Pampuri, Cristina De Luca, Giuseppe De Nicolao:
Nonparametric Virtual Sensors for Semiconductor Manufacturing - Using Information Theoretic Learning and Kernel Machines. ICINCO (2) 2011: 349-358 - Hanlin Goh, Lukasz Kusmierz, Joo-Hwee Lim, Nicolas Thome, Matthieu Cord:
Learning invariant color features with sparse topographic restricted Boltzmann machines. ICIP 2011: 1241-1244 - Priscila Saboia, Tiago Jose de Carvalho, Anderson Rocha:
Eye specular highlights telltales for digital forensics: A machine learning approach. ICIP 2011: 1937-1940 - Manish Narwaria, Weisi Lin:
Machine learning based modeling of spatial and temporal factors for video quality assessment. ICIP 2011: 2513-2516 - Wen-Fu Lee, Tai-Hsiang Huang, Su-Ling Yeh, Homer H. Chen:
Fusion of visual attention cues by machine learning. ICIP 2011: 3301-3304 - Manish Narwaria, Weisi Lin:
Video quality assessment using temporal quality variations and machine learning. ICME 2011: 1-6 - Jesús González-Rubio, Daniel Ortiz-Martínez, Francisco Casacuberta:
An active learning scenario for interactive machine translation. ICMI 2011: 197-200 - KyungHyun Cho, Tapani Raiko, Alexander Ilin:
Enhanced Gradient and Adaptive Learning Rate for Training Restricted Boltzmann Machines. ICML 2011: 105-112 - Arvind K. Sujeeth, HyoukJoong Lee, Kevin J. Brown, Tiark Rompf, Hassan Chafi, Michael Wu, Anand R. Atreya, Martin Odersky, Kunle Olukotun:
OptiML: An Implicitly Parallel Domain-Specific Language for Machine Learning. ICML 2011: 609-616 - Jeffrey Ellen, Shibin Parameswaran:
Machine Learning for Author Affiliation within Web Forums - Using Statistical Techniques on NLP Features for Online Group Identification. ICMLA (1) 2011: 100-105 - Krishnaveni Palaniappan, Sumitra Mukherjee:
Predicting "Essential" Genes across Microbial Genomes: A Machine Learning Approach. ICMLA (2) 2011: 189-194 - Georgi I. Nalbantov, Andre Dekker, Dirk De Ruysscher, Philippe Lambin, Evgueni N. Smirnov:
The Combination of Clinical, Dose-Related and Imaging Features Helps Predict Radiation-Induced Normal-Tissue Toxicity in Lung-cancer Patients - An in-silico Trial Using Machine Learning Techniques. ICMLA (2) 2011: 220-224 - Hisao Ishibuchi, Shingo Mihara, Yusuke Nojima:
Training Data Subdivision and Periodical Rotation in Hybrid Fuzzy Genetics-Based Machine Learning. ICMLA (1) 2011: 229-234 - Kelly Reynolds, April Kontostathis, Lynne Edwards:
Using Machine Learning to Detect Cyberbullying. ICMLA (2) 2011: 241-244 - Halil-Ibrahim Bulbul, Özkan Ünsal:
Comparison of Classification Techniques used in Machine Learning as Applied on Vocational Guidance Data. ICMLA (2) 2011: 298-301 - Jian Zhang:
Deep Transfer Learning via Restricted Boltzmann Machine for Document Classification. ICMLA (1) 2011: 323-326 - Yohei Okada, Shingo Ata, Nobuyuki Nakamura, Yoshihiro Nakahira, Ikuo Oka:
Comparisons of Machine Learning Algorithms for Application Identification of Encrypted Traffic. ICMLA (2) 2011: 358-361 - Juan Ramirez Jr., François G. Meyer:
Machine Learning for Seismic Signal Processing: Phase Classification on a Manifold. ICMLA (1) 2011: 382-388 - Yu-Xin Meng:
The practice on using machine learning for network anomaly intrusion detection. ICMLC 2011: 576-581 - Herman Chan, Mingjing Yang, Huiru Zheng, Haiying Wang, Roy Sterritt, Sally I. McClean:
Machine learning and statistical approaches to assessing gait patterns of younger and older healthy adults climbing stairs. ICNC 2011: 588-592 - Shu-Xia Lu, Xiaoxue Fan, Lisha Hu:
Learning the parameters for least squares support vector machine. ICNC 2011: 1527-1531 - Yating Hsu, David Lee:
Machine learning for implanted malicious code detection with incompletely specified system implementations. ICNP 2011: 31-36 - Keem Siah Yap:
A new multi agent system based on online sequential extreme learning machines and Bayesian Formalism. ICNSC 2011: 74-79 - Shuichi Matsuzaki, Yusuke Shiina, Yasuhiro Wada:
Adaptive Classification for Brain-Machine Interface with Reinforcement Learning. ICONIP (1) 2011: 360-369 - Stefano Ghidoni, Matteo Finotto, Emanuele Menegatti:
Self-learning visual inspection system for cable crimping machines. ICRA 2011 - Catalina-Lucia Cocianu, Luminita State, Panayiotis Vlamos:
A New Method for Learning the Support Vector Machines. ICSOFT (2) 2011: 365-370 - Hakim Lounis, Tamer Fares Gayed, Mounir Boukadoum:
Machine-Learning Models for Software Quality: A Compromise between Performance and Intelligibility. ICTAI 2011: 919-921 - Joo-Young Lee, Gumwon Hong, Hae-Chang Rim, Young-In Song, Young-Sook Hwang:
Predicate-argument reordering based on learning to rank for English-Korean machine translation. ICUIMC 2011: 2 - Marco Pennacchiotti, Ana-Maria Popescu:
A Machine Learning Approach to Twitter User Classification. ICWSM 2011 - Llanos Mora López, Ildefonso Martínez-Marchena, Michel Piliougine, Mariano Sidrach de Cardona:
Binding Statistical and Machine Learning Models for Short-Term Forecasting of Global Solar Radiation. IDA 2011: 294-305 - Tadeusz Witkowski, Pawel Antczak, Arkadiusz Antczak:
Machine learning - Based classification in manufacturing system. IDAACS (2) 2011: 580-585 - Vladimir Simov Jotsov:
Machine self-learning applications in security systems. IDAACS (2) 2011: 727-732 - Alireza Amini, Reza Tavakkoli-Moghaddam, Fardad Niakan:
A multi-objective identical parallel machine scheduling with setup and removal times with deteriorating and learning effects. IEEM 2011: 1271-1274 - Maria Koutina, Katia Lida Kermanidis:
Predicting Postgraduate Students' Performance Using Machine Learning Techniques. EANN/AIAI (2) 2011: 159-168 - R. Close, Joseph N. Wilson, Paul D. Gader:
A Bayesian approach to localized multi-kernel learning using the relevance vector machine. IGARSS 2011: 1103-1106 - Saleema Amershi, Bongshin Lee, Ashish Kapoor, Ratul Mahajan, Blaine Christian:
Human-Guided Machine Learning for Fast and Accurate Network Alarm Triage. IJCAI 2011: 2564-2569 - Márcio Dorn, Luciana S. Buriol, Luís C. Lamb:
Combining Machine Learning and Optimization Techniques to Determine 3-D Structures of Polypeptides. IJCAI 2011: 2794-2795 - Plamen P. Angelov:
Autonomous Learning Machines - Generating Rules from Data Streams. IJCCI (NCTA) 2011: 21 - Seyed Abolghasem Mirroshandel, Gholamreza Ghassem-Sani, Alexis Nasr:
Active Learning Strategies for Support Vector Machines, Application to Temporal Relation Classification. IJCNLP 2011: 56-64 - Piyabute Fuangkhon, Thitipong Tanprasert:
An Outpost Vector placement evaluation of an incremental learning algorithm for Support Vector Machine. IJCNN 2011: 254-261 - B. V. Phani, Bala Chandra, Vijay Raghav:
Quest for efficient option pricing prediction model using machine learning techniques. IJCNN 2011: 654-657 - Alireza Tamaddoni-Nezhad, David Bohan, Alan Raybould, Stephen H. Muggleton:
Machine Learning a Probabilistic Network of Ecological Interactions. ILP 2011: 332-346 - Abul Bashar, Gerard Parr, Sally I. McClean, Bryan W. Scotney, Detlef Nauck:
Novel distributed call admission control solution based on machine learning approach. Integrated Network Management 2011: 871-881 - Terrence Ziemniak:
Use of Machine Learning Classification Techniques to Detect Atypical Behavior in Medical Applications. IMF 2011: 149-162 - Torben Godsk, Mikkel Baun Kjærgaard:
High Classification Rates for Continuous Cow Activity Recognition Using Low-Cost GPS Positioning Sensors and Standard Machine Learning Techniques. ICDM 2011: 174-188 - Steven M. Drucker, Danyel Fisher, Sumit Basu:
Helping Users Sort Faster with Adaptive Machine Learning Recommendations. INTERACT (3) 2011: 187-203 - Johann Schrammel:
Exploring New Ways of Utilizing Automated Clustering and Machine Learning Techniques in Information Visualization. INTERACT (4) 2011: 394-397 - Haoyong Lv, Hengyao Tang:
Machine Learning Methods and Their Application Research. IPTC 2011: 108-110 - Teresa Maria Altomare Basile, Floriana Esposito, Stefano Ferilli:
Improving User Stereotypes through Machine Learning Techniques. IRCDL 2011: 38-48 - David Mayerich, Jaerock Kwon, Aaron Panchal, John Keyser, Yoonsuck Choe:
Fast cell detection in high-throughput imagery using GPU-accelerated machine learning. ISBI 2011: 719-723 - Christos Davatzikos:
Statistical atlases and machine learning tools applied to optimized prostate biopsy for cancer detection and estimation of volume and Gleason score. ISBI 2011: 2107-2108 - Mohamed Badreddine, Yves Blaquière, Mounir Boukadoum:
Machine-learning framework for automatic netlist creation. ISCAS 2011: 2865-2868 - Rozniza Ali, Amir Hussain, James E. Bron, Andrew P. Shinn:
Multi-stage classification of Gyrodactylus species using machine learning and feature selection techniques. ISDA 2011: 457-462 - Hyun Joon Jung, J. K. Aggarwal:
A Binary Stock Event Model for stock trends forecasting: Forecasting stock trends via a simple and accurate approach with machine learning. ISDA 2011: 714-719 - Michael Scott Cuthbert, Christopher Ariza, Lisa Friedland:
Feature Extraction and Machine Learning on Symbolic Music using the music21 Toolkit. ISMIR 2011: 387-392 - Luc De Raedt, Siegfried Nijssen:
Towards Programming Languages for Machine Learning and Data Mining (Extended Abstract). ISMIS 2011: 25-32 - Amel Bennaceur, Valérie Issarny, Richard Johansson, Alessandro Moschitti, Daniel Sykes, Romina Spalazzese:
Machine Learning for Automatic Classification of Web Service Interface Descriptions. ISoLA Workshops 2011: 220-231 - Jen-Yi Wuu, Fedor G. Pikus, Malgorzata Marek-Sadowska:
Metrics for characterizing machine learning-based hotspot detection methods. ISQED 2011: 116-121 - José Luis García Arroyo, Begoña García Zapirain, Amaia Méndez Zorrilla:
Blue-white veil and dark-red patch of pigment pattern recognition in dermoscopic images using machine-learning techniques. ISSPIT 2011: 196-201 - Michael Goldweber:
Two kinesthetic learning activities: turing machines and basic computer organization. ITiCSE 2011: 335 - M. Zubair Rafique, Zeeshan Shafi Khan, Muhammad Khurram Khan, Khaled Alghathbar:
Securing IP-Multimedia Subsystem (IMS) against Anomalous Message Exploits by Using Machine Learning Algorithms. ITNG 2011: 559-563 - A. Paniagua-Tineo, Sancho Salcedo-Sanz, Emilio G. Ortíz-García, J. Gascón-Moreno, B. Saavedra-Moreno, José Antonio Portilla-Figueras:
On the Performance of the μ-GA Extreme Learning Machines in Regression Problems. IWANN (2) 2011: 153-160 - João P. Papa, Clayton R. Pereira, Victor Hugo C. de Albuquerque, Cleiton C. Silva, Alexandre X. Falcão, João Manuel R. S. Tavares:
Precipitates Segmentation from Scanning Electron Microscope Images through Machine Learning Techniques. IWCIA 2011: 456-468 - Michael Slavik, Imad Mahgoub:
Applying machine learning to the design of multi-hop broadcast protocols for VANET. IWCMC 2011: 1742-1747 - Hakim Lounis, Tamer Fares Gayed, Mounir Boukadoum:
Using Efficient Machine-Learning Models to Assess Two Important Quality Factors: Maintainability and Reusability. IWSM/Mensura 2011: 170-177 - Heather Leary, Mimi Recker, Andrew E. Walker, Philipp G. Wetzler, Tamara Sumner, James H. Martin:
Automating open educational resources assessments: a machine learning generalization study. JCDL 2011: 283-286 - Matthias Grabmair, Kevin D. Ashley, Rebecca Hwa, Patricia M. Sweeney:
Toward Extracting Information from Public Health Statutes using Text Classification Machine Learning. JURIX 2011: 73-82 - Ning Chen, Steven C. H. Hoi, Xiaokui Xiao:
Software process evaluation: A machine learning approach. ASE 2011: 333-342 - Amol Ghoting, Prabhanjan Kambadur, Edwin P. D. Pednault, Ramakrishnan Kannan:
NIMBLE: a toolkit for the implementation of parallel data mining and machine learning algorithms on mapreduce. KDD 2011: 334-342 - Duen Horng Chau, Aniket Kittur, Jason I. Hong, Christos Faloutsos:
Apolo: interactive large graph sensemaking by combining machine learning and visualization. KDD 2011: 739-742 - Ravi Vijayaraghavan, P. V. Kannan:
Applications of data mining and machine learning in online customer care. KDD 2011: 779 - Sebastian Zander, Grenville J. Armitage:
Practical machine learning based multimedia traffic classification for distributed QoS management. LCN 2011: 399-406 - Scott Vanderbeck, Joseph Bockhorst, Chad Oldfather:
A Machine Learning Approach to Identifying Sections in Legal Briefs. MAICS 2011: 16-22 - Xiangping Bu, Jia Rao, Cheng-Zhong Xu:
A Model-free Learning Approach for Coordinated Configuration of Virtual Machines and Appliances. MASCOTS 2011: 12-21 - Manuel Stritt, Roman Bär, Joël Freyss, Julia Marrie, Enrico Vezzali, Edgar Weber, Anna Stalder:
Supervised Machine Learning Methods for Quantification of Pulmonary Fibrosis. MDA 2011: 24-37 - Theodoros Anagnostopoulos, Christos Anagnostopoulos, Stathes Hadjiefthymiades:
Mobility Prediction Based on Machine Learning. Mobile Data Management (2) 2011: 27-30 - Anne-Laure Fouque, Pierre Fillard, Anne Bargiacchi, Arnaud Cachia, Monica Zilbovicius, Benjamin Thyreau, Edith Le Floch, Philippe Ciuciu, Edouard Duchesnay:
Voxelwise Multivariate Statistics and Brain-Wide Machine Learning Using the Full Diffusion Tensor. MICCAI (2) 2011: 9-16 - Lisa Tang, Ghassan Hamarneh, Tim Bressmann:
A Machine Learning Approach to Tongue Motion Analysis in 2D Ultrasound Image Sequences. MLMI 2011: 151-158 - Ayse Betül Oktay, Yusuf Sinan Akgul:
Localization of the Lumbar Discs Using Machine Learning and Exact Probabilistic Inference. MICCAI (3) 2011: 158-165 - Kunlei Zhang, Wenmiao Lu:
Automatic Human Knee Cartilage Segmentation from Multi-contrast MR Images Using Extreme Learning Machines and Discriminative Random Fields. MLMI 2011: 335-343 - Jianwu Xu, Kenji Suzuki:
Computer-Aided Detection of Polyps in CT Colonography with Pixel-Based Machine Learning Techniques. MLMI 2011: 360-367 - Josip Hucaljuk, Alen Rakipovic:
Predicting football scores using machine learning techniques. MIPRO 2011: 1623-1627 - Mladen Marovic, Marko Mihokovic, Mladen Miksa, Sinisa Pribil, Alan Tus:
Automatic movie ratings prediction using machine learning. MIPRO 2011: 1640-1645 - Jitendra Kumar Rai, Atul Negi, Rajeev Wankar:
Machine Learning Based Performance Prediction for Multi-core Simulation. MIWAI 2011: 236-247 - Douglas A. Talbert, Matt Honeycutt, Steve Talbert:
A Machine Learning and Data Mining Framework to Enable Evolutionary Improvement in Trauma Triage. MLDM 2011: 348-361 - Javier Alonso, Lluís Belanche, Dimiter R. Avresky:
Predicting Software Anomalies Using Machine Learning Techniques. NCA 2011: 163-170 - Marin Marinov, Dimiter R. Avresky:
Machine Learning Techniques for Predicting Web Server Anomalies. NCCA 2011: 114-120 - Cynthia Wagner, Jérôme François, Radu State, Thomas Engel:
Machine Learning Approach for IP-Flow Record Anomaly Detection. Networking (1) 2011: 28-39 - Nicholas Gillian, Benjamin Knapp, Sile O'Modhrain:
A Machine Learning Toolbox For Musician Computer Interaction. NIME 2011: 343-348 - Margaret Schedel, Phoenix Perry, Rebecca Fiebrink:
Wekinating 000000Swan: Using Machine Learning to Create and Control Complex Artistic Systems. NIME 2011: 453-456 - Francis R. Bach, Eric Moulines:
Non-Asymptotic Analysis of Stochastic Approximation Algorithms for Machine Learning. NIPS 2011: 451-459 - Matthew A. Kayala, Pierre Baldi:
A Machine Learning Approach to Predict Chemical Reactions. NIPS 2011: 747-755 - Minh Quang Nhat Pham, Minh Le Nguyen, Akira Shimazu:
A Machine Learning based Textual Entailment Recognition System of JAIST Team for NTCIR9 RITE. NTCIR 2011 - A. Paniagua-Tineo, Sancho Salcedo-Sanz, Emilio G. Ortíz-García, Antonio Portilla-Figueras, B. Saavedra-Moreno, G. López-Díaz:
Greenhouse Indoor Temperature Prediction Based on Extreme Learning Machines for Resource-Constrained Control Devices Implementation. PAAMS (Special Sessions) 2011: 203-211 - José M. Urquiza, Ignacio Rojas, Héctor Pomares, Luis Javier Herrera, J. P. Florido, Francisco M. Ortuño Guzman:
Using Machine Learning Techniques and Genomic/Proteomic Information from Known Databases for PPI Prediction. PACBB 2011: 373-380 - Xiaoyuan Su, Russell Greiner, Taghi M. Khoshgoftaar, Amri Napolitano:
Using Classifier-Based Nominal Imputation to Improve Machine Learning. PAKDD (1) 2011: 124-135 - Tapio Pahikkala, Antti Airola, Thomas Canhao Xu, Pasi Liljeberg, Hannu Tenhunen, Tapio Salakoski:
A Parallel Online Regularized Least-squares Machine Learning Algorithm for Future Multi-core Processors. PECCS 2011: 590-599 - Christopher M. Bishop:
Embracing Uncertainty: Applied Machine Learning Comes of Age. ECML/PKDD (1) 2011: 4 - Ivan Shamshurin:
Data Representation in Machine Learning-Based Sentiment Analysis of Customer Reviews. PReMI 2011: 254-260 - Sergey Golubev:
Construction of Model of Structured Documents Based on Machine Learning. PReMI 2011: 424-431 - Leandro L. Minku, Xin Yao:
A principled evaluation of ensembles of learning machines for software effort estimation. PROMISE 2011: 9 - Sherif Saad, Issa Traoré, Ali A. Ghorbani, Bassam Sayed, David Zhao, Wei Lu, John Felix, Payman Hakimian:
Detecting P2P botnets through network behavior analysis and machine learning. PST 2011: 174-180 - Miquel Esplà-Gomis, Víctor M. Sánchez-Cartagena, Juan Antonio Pérez-Ortiz:
Enlarging Monolingual Dictionaries for Machine Translation with Active Learning and Non-Expert Users. RANLP 2011: 339-346 - Marco Turchi, Vanni Zavarella, Hristo Tanev:
Pattern Learning for Event Extraction using Monolingual Statistical Machine Translation. RANLP 2011: 371-377 - Liviu Petrisor Dinu, Emil Ionescu, Vlad Niculae, Octavia-Maria Sulea:
Can Alternations Be Learned? A Machine Learning Approach To Romanian Verb Conjugation. RANLP 2011: 539-544 - Urun Dogan, Johann Edelbrunner, Ioannis Iossifidis:
Autonomous driving: A comparison of machine learning techniques by means of the prediction of lane change behavior. ROBIO 2011: 1837-1843 - Lev Itskovich, Sergei Kuznetsov:
Machine Learning Methods in Character Recognition. RSFDGrC 2011: 322-329 - Aditya V. Nori, Sriram K. Rajamani:
Program Analysis and Machine Learning: A Win-Win Deal. SAS 2011: 2-3 - James Herold, Thomas F. Stahovich:
ClassySeg: A Machine Learning Approach to AutomaticStroke Segmentation. SBM 2011: 109-116 - Georg Ruß, Rudolf Kruse:
Machine Learning Methods for Spatial Clustering on Precision Agriculture Data. SCAI 2011: 40-49 - Giuseppe Tradigo, Pierangelo Veltri, Gianluca Pollastri:
Machine Learning Approaches for Contact Maps Prediction in CASP9 Experiment. SEBD 2011: 311-317 - Mahdi Noorian, Ebrahim Bagheri, Weichang Du:
Machine Learning-based Software Testing: Towards a Classification Framework. SEKE 2011: 225-229 - Asif Ekbal, Amit Majumder, Mohammed Hasanuzzaman, Sriparna Saha:
Supervised Machine Learning Approach for Bio-molecular Event Extraction. SEMCCO (2) 2011: 231-238 - Alex Chengyu Fang, Harry Bunt, Jing Cao, Xiaoyue Liu:
Relating the Semantics of Dialogue Acts to Linguistic Properties: A Machine Learning Perspective through Lexical Cues. ICSC 2011: 490-497 - Dennis Spohr, Laura Hollink, Philipp Cimiano:
A Machine Learning Approach to Multilingual and Cross-Lingual Ontology Matching. International Semantic Web Conference (1) 2011: 665-680 - Alessandro Moschitti:
Kernel-Based Machines for Abstract and Easy Modeling of Automatic Learning. SFM 2011: 458-503 - Daoud Clarke, Peter C. R. Lane, Paul Hender:
Semi-Automatic Analysis of Traditional Media with Machine Learning. SGAI Conf. 2011: 325-337 - Srinivasan Janarthanam, Helen Wright Hastie, Oliver Lemon, Xingkun Liu:
"The day after the day after tomorrow?" A machine learning approach to adaptive temporal expression generation: training and evaluation with real users. SIGDIAL Conference 2011: 142-151 - Yuan Lin, Hongfei Lin, Song Jin, Zheng Ye:
Social annotation in query expansion: a machine learning approach. SIGIR 2011: 405-414 - Yanxin Shi, David Ye, Andrey Goder, Srinivas Narayanan:
A large scale machine learning system for recommending heterogeneous content in social networks. SIGIR 2011: 1337-1338 - ZhangBing Zhou, Mohamed Sellami, Walid Gaaloul, Bruno Defude:
Clustering and Managing Data Providing Services Using Machine Learning Technique. SKG 2011: 225-232 - Yeon-Jun Kim, Mark C. Beutnagel:
Automatic assessment of american English lexical stress using machine learning algorithms. SLaTE 2011: 93-96 - Navin Sharma, Pranshu Sharma, David E. Irwin, Prashant J. Shenoy:
Predicting solar generation from weather forecasts using machine learning. SmartGridComm 2011: 528-533 - Ioannis Kaloskampis, Yulia Hicks, A. David Marshall:
Reinforcing conceptual engineering design with a hybrid computer vision, machine learning and knowledge based system framework. SMC 2011: 3242-3249 - Michael Brennan, Rachel Greenstadt:
Coalescing Twitter Trends: The Under-Utilization of Machine Learning in Social Media. SocialCom/PASSAT 2011: 641-646 - Antonina Danylenko, Christoph W. Kessler, Welf Löwe:
Comparing Machine Learning Approaches for Context-Aware Composition. Software Composition 2011: 18-33 - Ahmad A. Al Sallab, Mohsen A. Rashwan:
Self learning machines using Deep Networks. SoCPaR 2011: 21-26 - Jorge de la Calleja, Antonio Benítez, Ma. Auxilio Medina, Olac Fuentes:
Machine learning from imbalanced data sets for astronomical object classification. SoCPaR 2011: 435-439 - Lars Kotthoff, Ian P. Gent, Ian Miguel:
A Preliminary Evaluation of Machine Learning in Algorithm Selection for Search Problems. SOCS 2011 - Xiaofeng Liao, Liping Ding, Yongji Wang:
Secure Machine Learning, a Brief Overview. SSIRI (Companion) 2011: 26-29 - Josef Urban, Jirí Vyskocil, Petr Stepánek:
MaLeCoP Machine Learning Connection Prover. TABLEAUX 2011: 263-277 - Barnabás Póczos, Liang Xiong, Jeff G. Schneider:
Nonparametric Divergence Estimation with Applications to Machine Learning on Distributions. UAI 2011: 599-608 - Saleema Amershi:
Designing for effective end-user interaction with machine learning. UIST (Adjunct Volume) 2011: 47-50 - Ahmad Ammari, Vania Dimitrova, Dimoklis Despotakis:
Identifying Relevant YouTube Comments to Derive Socially Augmented User Models: A Semantically Enriched Machine Learning Approach. UMAP Workshops 2011: 71-85 - Fabian Yamaguchi, Felix F. X. Lindner, Konrad Rieck:
Vulnerability Extrapolation: Assisted Discovery of Vulnerabilities Using Machine Learning. WOOT 2011: 118-127 - Sebastián Marbán, Cyriel Rutten, Tjark Vredeveld:
Learning in Stochastic Machine Scheduling. WAOA 2011: 21-34 - Guangyong Gao, Guoping Jiang:
A zero-watermarking image authentication scheme using Zernike moment and extreme learning machine. WCSP 2011: 1-5 - Nikolaos Mallios, Elpiniki I. Papageorgiou, Michael Samarinas:
Comparison of Machine Learning Techniques using the WEKA Environment for Prostate Cancer Therapy Plan. WETICE 2011: 151-155 - Hongbo Shi, Tomoki Hamagami, Haoyuan Xu:
Machine Learning Based Autonomous Network Flow Identifying Method. WICON 2011: 447-457 - Amine Chohra, Felicita Di Giandomenico, Stefano Porcarelli, Andrea Bondavalli:
An Intelligent Maintenance based on Machine Learning Approach for Wireless and Mobile Systems. WINSYS 2011: 115-118 - Jie Yang, Yuanhao Wu, Yinan Dou, Kun Zhang:
Robustness Promotion of High Speed Network Content Auditing Integrated System Based on Machine Learning Method. WISM (1) 2011: 411-418 - Min Jou, Yu-Shiang Wu:
Designing a Web-Based VR Machine for Learning of Packaging and Testing Skills. WSKS 2011: 567-573 - Filippo Caschera, Steen Rasmussen, Martin M. Hanczyc:
Machine Learning Optimization of Evolvable Artificial Cells. FET 2011: 187-189 - Marko Grobelnik, Dunja Mladenic, Gregor Leban, Tadej Stajner:
Machine Learning Techniques for Understanding Context and Process. Context and Semantics for Knowledge Management 2011: 127-145 - Rayid Ghani, Divna Djordjevic, Chad M. Cumby:
Machine Learning and Lightweight Semantics to Improve Enterprise Search and Knowledge Management. Context and Semantics for Knowledge Management 2011: 171-188 - Frank Wittig:
Comparison of Machine Learning Techniques for Bayesian Networks for User-Adaptive Systems. Resource-Adaptive Cognitive Processes 2011: 315-336 - Raymond S. Smith, Terry Windeatt:
Facial Action Unit Recognition Using Filtered Local Binary Pattern Features with Bootstrapped and Weighted ECOC Classifiers. Ensembles in Machine Learning Applications 2011: 1-20 - Miguel Ángel Bautista, Sergio Escalera, Xavier Baró, Oriol Pujol, Jordi Vitrià, Petia Radeva:
On the Design of Low Redundancy Error-Correcting Output Codes. Ensembles in Machine Learning Applications 2011: 21-38 - Evgueni N. Smirnov, Matthijs Moed, Georgi I. Nalbantov, Ida G. Sprinkhuizen-Kuyper:
Minimally-Sized Balanced Decomposition Schemes for Multi-class Classification. Ensembles in Machine Learning Applications 2011: 39-58 - Cemre Zor, Terry Windeatt, Berrin A. Yanikoglu:
Bias-Variance Analysis of ECOC and Bagging Using Neural Nets. Ensembles in Machine Learning Applications 2011: 59-73 - Stefano Ferilli, Teresa Maria Altomare Basile, Nicola Di Mauro, Floriana Esposito:
Automatic Document Layout Analysis through Relational Machine Learning. Learning Structure and Schemas from Documents 2011: 73-96 - Benjamin Schowe, Katharina Morik:
Fast-Ensembles of Minimum Redundancy Feature Selection. Ensembles in Machine Learning Applications 2011: 75-95 - Rakkrit Duangsoithong, Terry Windeatt:
Hybrid Correlation and Causal Feature Selection for Ensemble Classifiers. Ensembles in Machine Learning Applications 2011: 97-115 - Houtao Deng, Saylisse Dávila, George C. Runger, Eugene Tuv:
Learning Markov Blankets for Continuous or Discrete Networks via Feature Selection. Ensembles in Machine Learning Applications 2011: 117-131 - Stefano Ceccon, David Garway-Heath, David P. Crabb, Allan Tucker:
Ensembles of Bayesian Network Classifiers Using Glaucoma Data and Expertise. Ensembles in Machine Learning Applications 2011: 133-150 - Alessandro Rozza, Gabriele Lombardi, Matteo Re, Elena Casiraghi, Giorgio Valentini, Paola Campadelli:
A Novel Ensemble Technique for Protein Subcellular Location Prediction. Ensembles in Machine Learning Applications 2011: 151-167 - Haytham Elghazel, Alex Aussem, Florence Perraud:
Trading-Off Diversity and Accuracy for Optimal Ensemble Tree Selection in Random Forests. Ensembles in Machine Learning Applications 2011: 169-179 - Carlos Pardo, Juan J. Rodríguez Diez, José-Francisco Díez-Pastor, Cesar García-Osorio:
Random Oracles for Regression Ensembles. Ensembles in Machine Learning Applications 2011: 181-199 - Pierluigi Casale, Oriol Pujol, Petia Radeva:
Embedding Random Projections in Regularized Gradient Boosting Machines. Ensembles in Machine Learning Applications 2011: 201-216 - Giuliano Armano, Nima Hatami:
An Improved Mixture of Experts Model: Divide and Conquer Using Random Prototypes. Ensembles in Machine Learning Applications 2011: 217-231 - Ricardo Bastos Cavalcante Prudêncio, Marcilio C. P. de Souto, Teresa Bernarda Ludermir:
Selecting Machine Learning Algorithms Using the Ranking Meta-Learning Approach. Meta-Learning in Computational Intelligence 2011: 225-243 - Indre Zliobaite:
Three Data Partitioning Strategies for Building Local Classifiers. Ensembles in Machine Learning Applications 2011: 233-250 - Cristina Versino, Paolo Lombardi:
Filtering Surveillance Image Streams by Interactive Machine Learning. Multimedia Analysis, Processing and Communications 2011: 289-325 - Chun-Nan Hsu, Wee Sun Lee:
Proceedings of the 3rd Asian Conference on Machine Learning, ACML 2011, Taoyuan, Taiwan, November 13-15, 2011. JMLR Proceedings 20, JMLR.org 2011 [contents] - Clara Pizzuti, Marylyn D. Ritchie, Mario Giacobini:
Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics - 9th European Conference, EvoBIO 2011, Torino, Italy, April 27-29, 2011. Proceedings. Lecture Notes in Computer Science 6623, Springer 2011, ISBN 978-3-642-20388-6 [contents] - Timo Honkela, Wlodzislaw Duch, Mark A. Girolami, Samuel Kaski:
Artificial Neural Networks and Machine Learning - ICANN 2011 - 21st International Conference on Artificial Neural Networks, Espoo, Finland, June 14-17, 2011, Proceedings, Part I. Lecture Notes in Computer Science 6791, Springer 2011, ISBN 978-3-642-21734-0 [contents] - Timo Honkela, Wlodzislaw Duch, Mark A. Girolami, Samuel Kaski:
Artificial Neural Networks and Machine Learning - ICANN 2011 - 21st International Conference on Artificial Neural Networks, Espoo, Finland, June 14-17, 2011, Proceedings, Part II. Lecture Notes in Computer Science 6792, Springer 2011, ISBN 978-3-642-21737-1 [contents] - Lise Getoor, Tobias Scheffer:
Proceedings of the 28th International Conference on Machine Learning, ICML 2011, Bellevue, Washington, USA, June 28 - July 2, 2011. Omnipress 2011 [contents] - Xue-wen Chen, Tharam S. Dillon, Hisao Ishbuchi, Jian Pei, Haixun Wang, M. Arif Wani:
10th International Conference on Machine Learning and Applications and Workshops, ICMLA 2011, Honolulu, Hawaii, USA, December 18-21, 2011. Volume 1: Main Conference. IEEE Computer Society 2011, ISBN 978-0-7695-4607-0 [contents] - Xue-wen Chen, Tharam S. Dillon, Hisao Ishbuchi, Jian Pei, Haixun Wang, M. Arif Wani:
10th International Conference on Machine Learning and Applications and Workshops, ICMLA 2011, Honolulu, Hawaii, USA, December 18-21, 2011. Volume 2: Special Sessions and Workshop. IEEE Computer Society 2011 [contents] - International Conference on Machine Learning and Cybernetics, ICMLC 2011, Guilin, China, July 10-13, 2011, Proceedings. IEEE 2011, ISBN 978-1-4577-0305-8 [contents]
- Kenji Suzuki, Fei Wang, Dinggang Shen, Pingkun Yan:
Machine Learning in Medical Imaging - Second International Workshop, MLMI 2011, Held in Conjunction with MICCAI 2011, Toronto, Canada, September 18, 2011. Proceedings. Lecture Notes in Computer Science 7009, Springer 2011, ISBN 978-3-642-24318-9 [contents] - Petra Perner:
Machine Learning and Data Mining in Pattern Recognition - 7th International Conference, MLDM 2011, New York, NY, USA, August 30 - September 3, 2011. Proceedings. Lecture Notes in Computer Science 6871, Springer 2011, ISBN 978-3-642-23198-8 [contents] - Petra Perner:
Machine Learning and Data Mining in Pattern Recognition, 7th International Conference, MLDM 2011, New York, USA, September/August 2011, Poster Proceedings. IBaI Publishing 2011, ISBN 978-3-942952-03-3 [contents] - 2011 Symposium on Machine Learning in Speech and Language Processing, MLSLP 2011, Bellevue, WA, USA, June 27, 2011. ISCA 2011 [contents]
- Christos Dimitrakakis, Aris Gkoulalas-Divanis, Aikaterini Mitrokotsa, Vassilios S. Verykios, Yücel Saygin:
Privacy and Security Issues in Data Mining and Machine Learning - International ECML/PKDD Workshop, PSDML 2010, Barcelona, Spain, September 24, 2010. Revised Selected Papers. Lecture Notes in Computer Science 6549, Springer 2011, ISBN 978-3-642-19895-3 [contents] - Dimitrios Gunopulos, Thomas Hofmann, Donato Malerba, Michalis Vazirgiannis:
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2011, Athens, Greece, September 5-9, 2011. Proceedings, Part I. Lecture Notes in Computer Science 6911, Springer 2011, ISBN 978-3-642-23779-9 [contents] - Dimitrios Gunopulos, Thomas Hofmann, Donato Malerba, Michalis Vazirgiannis:
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2011, Athens, Greece, September 5-9, 2011, Proceedings, Part II. Lecture Notes in Computer Science 6912, Springer 2011, ISBN 978-3-642-23782-9 [contents] - Dimitrios Gunopulos, Thomas Hofmann, Donato Malerba, Michalis Vazirgiannis:
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2011, Athens, Greece, September 5-9, 2011, Proceedings, Part III. Lecture Notes in Computer Science 6913, Springer 2011, ISBN 978-3-642-23807-9 [contents] - Oleg Okun, Giorgio Valentini, Matteo Ré:
Ensembles in Machine Learning Applications. Studies in Computational Intelligence 373, Springer 2011, ISBN 978-3-642-22909-1 [contents] - Xin Liu, Gilles Trédan, Anwitaman Datta:
A generic trust framework for large-scale open systems using machine learning. CoRR abs/1103.0086 (2011) - Hamed Hassanzadeh, Mohammad Reza Keyvanpour:
A Machine Learning Based Analytical Framework for Semantic Annotation Requirements. CoRR abs/1104.4950 (2011) - Theja Tulabandhula, Cynthia Rudin, Patrick Jaillet:
Machine Learning and the Traveling Repairman. CoRR abs/1104.5061 (2011) - Craig A. Knoblock, Kristina Lerman, Steven Minton:
Wrapper Maintenance: A Machine Learning Approach. CoRR abs/1106.4872 (2011) - Jitesh Dundas, David Chik:
IBSEAD: - A Self-Evolving Self-Obsessed Learning Algorithm for Machine Learning. CoRR abs/1106.6186 (2011) - Yucheng Low, Joseph Gonzalez, Aapo Kyrola, Danny Bickson, Carlos Guestrin:
GraphLab: A Distributed Framework for Machine Learning in the Cloud. CoRR abs/1107.0922 (2011) - Yizhao Ni, Matt McVicar, Raúl Santos-Rodriguez, Tijl De Bie:
An end-to-end machine learning system for harmonic analysis of music. CoRR abs/1107.4969 (2011) - Byron Knoll, Nando de Freitas:
A Machine Learning Perspective on Predictive Coding with PAQ. CoRR abs/1108.3298 (2011) - Caleb Phillips, Lee Becker, Elizabeth Bradley:
Strange Beta: An Assistance System for Indoor Rock Climbing Route Setting Using Chaotic Variations and Machine Learning. CoRR abs/1110.0532 (2011) - Duncan A. J. Blythe:
Two Projection Pursuit Algorithms for Machine Learning under Non-Stationarity. CoRR abs/1110.0593 (2011) - Nicholas M. Ball:
Discussion on "Techniques for Massive-Data Machine Learning in Astronomy" by A. Gray. CoRR abs/1110.5688 (2011) - Song Liu, Peter A. Flach, Nello Cristianini:
Generic Multiplicative Methods for Implementing Machine Learning Algorithms on MapReduce. CoRR abs/1111.2111 (2011) - Theja Tulabandhula, Cynthia Rudin:
Machine Learning with Operational Costs. CoRR abs/1112.0698 (2011) - S. Malathi, S. Sridhar:
A Classical Fuzzy Approach for Software Effort Estimation on Machine Learning Technique. CoRR abs/1112.3877 (2011) - John C. Snyder, Matthias Rupp, Katja Hansen, Klaus-Robert Müller, Kieron Burke:
Finding Density Functionals with Machine Learning. CoRR abs/1112.5441 (2011) - Luc De Raedt, Siegfried Nijssen, Barry O'Sullivan, Pascal Van Hentenryck:
Constraint Programming meets Machine Learning and Data Mining (Dagstuhl Seminar 11201). Dagstuhl Reports 1(5): 61-83 (2011) - 2010
- Nello Cristianini, John Shawe-Taylor:
An Introduction to Support Vector Machines and Other Kernel-based Learning Methods. Cambridge University Press 2010, ISBN 978-0-521-78019-3, pp. I-XIII, 1-189 - Hendri Murfi:
Machine learning for text indexing: concept extraction, keyword extraction and tag recommendation. Berlin Institute of Technology 2010 - Edith Benedicta Maria Werner:
Learning finite state machine specifications from test cases. University of Göttingen 2010 - André Stuhlsatz:
Machine learning with Lipschitz classifiers. Otto von Guericke University Magdeburg 2010, pp. 1-200 - Markus Weimer:
Machine teaching: a machine learning approach to technology enhanced learning. Darmstadt University of Technology 2010, pp. 1-148 - Zheng Rong Yang:
Machine Learning Approaches to Bioinformatics. Science, Engineering, and Biology Informatics 4, World Scientific 2010, ISBN 978-981-4287-30-2, pp. 1-336 - Michael R. Genesereth:
Data Integration: The Relational Logic Approach. Synthesis Lectures on Artificial Intelligence and Machine Learning, Morgan & Claypool Publishers 2010 [contents] - Csaba Szepesvári:
Algorithms for Reinforcement Learning. Synthesis Lectures on Artificial Intelligence and Machine Learning, Morgan & Claypool Publishers 2010 [contents] - Paolo Priore, José Parreño, Raúl Pino, Alberto Gomez, Javier Puente:
Learning-Based Scheduling of Flexible Manufacturing Systems Using Support Vector Machines. Applied Artificial Intelligence 24(3): 194-209 (2010) - Christian Rieger, Barbara Zwicknagl:
Sampling inequalities for infinitely smooth functions, with applications to interpolation and machine learning. Adv. Comput. Math. 32(1): 103-129 (2010) - Djamel Bouchaffra, Abbes Amira, Ce Zhu, Chu-Song Chen:
Machine Learning Paradigms for Modeling Spatial and Temporal Information in Multimedia Data Mining. Adv. Artificial Intellegence 2010: 312350:1-312350:2 (2010) - Luca Pulina:
Engineering portfolios of Machine Learning algorithms to solve complex tasks in Robotics and Automated Reasoning. AI Commun. 23(1): 61-63 (2010) - Caroline Privault, Jacki O'Neill, Victor Ciriza, Jean-Michel Renders:
A new tangible user interface for machine learning document review. Artif. Intell. Law 18(4): 459-479 (2010) - Zhang Xingong, Yan Guangle:
Single-machine group scheduling problems with deteriorated and learning effect. Applied Mathematics and Computation 216(4): 1259-1266 (2010) - Ji-Bo Wang, Dan Wang, Guo-Dong Zhang:
Single-machine scheduling with learning functions. Applied Mathematics and Computation 216(4): 1280-1286 (2010) - Dehua Xu, Yunqiang Yin, Hongxing Li:
Comments on "A note on minimizing maximum lateness in an m-machine scheduling problem with a learning effect". Applied Mathematics and Computation 217(2): 939-943 (2010) - Suh-Jenq Yang:
Single-machine scheduling problems with both start-time dependent learning and position dependent aging effects under deteriorating maintenance consideration. Applied Mathematics and Computation 217(7): 3321-3329 (2010) - Maciej Troc, Olgierd Unold:
Self-adaptation of parameters in a learning classifier system ensemble machine. Applied Mathematics and Computer Science 20(1): 157-174 (2010) - Dursun Delen, Asil Oztekin, Zhenyu (James) Kong:
A machine learning-based approach to prognostic analysis of thoracic transplantations. Artificial Intelligence in Medicine 49(1): 33-42 (2010) - John Hayward, Sergio A. Alvarez, Carolina Ruiz, Mary Sullivan, Jennifer Tseng, Giles Whalen:
Machine learning of clinical performance in a pancreatic cancer database. Artificial Intelligence in Medicine 49(3): 187-195 (2010) - José M. Jerez, Ignacio Molina, Pedro J. García-Laencina, Emilio Alba, Nuria Ribelles, Miguel Martín, Leonardo Franco:
Missing data imputation using statistical and machine learning methods in a real breast cancer problem. Artificial Intelligence in Medicine 50(2): 105-115 (2010) - Chih-Fong Tsai, Ming-Lun Chen:
Credit rating by hybrid machine learning techniques. Appl. Soft Comput. 10(2): 374-380 (2010) - Jörg Wicker, Kathrin Fenner, Lynda B. M. Ellis, Lawrence P. Wackett, Stefan Kramer:
Predicting biodegradation products and pathways: a hybrid knowledge- and machine learning-based approach. Bioinformatics 26(6): 814-821 (2010) - Pedro J. Ballester, John B. O. Mitchell:
A machine learning approach to predicting protein-ligand binding affinity with applications to molecular docking. Bioinformatics 26(9): 1169-1175 (2010) - Wen-Han Yu, Hedda Høvik, Tsute Chen:
A hidden Markov support vector machine framework incorporating profile geometry learning for identifying microbial RNA in tiling array data. Bioinformatics 26(11): 1423-1430 (2010) - Anuj R. Shah, Khushbu Agarwal, Erin S. Baker, Mudita Singhal, Anoop M. Mayampurath, Yehia M. Ibrahim, Lars J. Kangas, Matthew E. Monroe, Rui Zhao, Mikhail E. Belov, Gordon A. Anderson, Richard D. Smith:
Machine learning based prediction for peptide drift times in ion mobility spectrometry. Bioinformatics 26(13): 1601-1607 (2010) - Joseph M. Dale, Liviu Popescu, Peter D. Karp:
Machine learning methods for metabolic pathway prediction. BMC Bioinformatics 11: 15 (2010) - Hatice U. Osmanbeyoglu, Jessica A. Wehner, Jaime G. Carbonell, Madhavi Ganapathiraju:
Active machine learning for transmembrane helix prediction. BMC Bioinformatics 11(S-1): 58 (2010) - Xiaojiang Xu, Stephen Hoang, Marty W. Mayo, Stefan Bekiranov:
Application of machine learning methods to histone methylation ChIP-Seq data reveals H4R3me2 globally represses gene expression. BMC Bioinformatics 11: 396 (2010) - Lance E. Palmer, Mathäus Dejori, Randall A. Bolanos, Daniel P. Fasulo:
Improving de novo sequence assembly using machine learning and comparative genomics for overlap correction. BMC Bioinformatics 11: 33 (2010) - Zafer Aydin, John I. Murray, Robert H. Waterston, William Stafford Noble:
Using machine learning to speed up manual image annotation: application to a 3D imaging protocol for measuring single cell gene expression in the developing C. elegans embryo. BMC Bioinformatics 11: 84 (2010) - Ashis Kumer Biswas, Nasimul Noman, Abdur Rahman Sikder:
Machine learning approach to predict protein phosphorylation sites by incorporating evolutionary information. BMC Bioinformatics 11: 273 (2010) - Martin Sturm, Michael Hackenberg, David Langenberger, Dmitrij Frishman:
TargetSpy: a supervised machine learning approach for microRNA target prediction. BMC Bioinformatics 11: 292 (2010) - Daniela Nitsch, Joana P. Gonçalves, Fabian Ojeda, Bart De Moor, Yves Moreau:
Candidate gene prioritization by network analysis of differential expression using machine learning approaches. BMC Bioinformatics 11: 460 (2010) - Morten Källberg, Hui Lu:
An improved machine learning protocol for the identification of correct Sequest search results. BMC Bioinformatics 11: 591 (2010) - Gary L. Rogers, Pablo Moscato, Michael A. Langston:
Graph algorithms for machine learning: a case-control study based on prostate cancer populations and high throughput transcriptomic data. BMC Bioinformatics 11(S-4): P21 (2010) - Giorgio Guzzetta, Giuseppe Jurman, Cesare Furlanello:
A machine learning pipeline for quantitative phenotype prediction from genotype data. BMC Bioinformatics 11(S-8): S3 (2010) - Yi Zhang, Kim A. Hatch, Joanna Bacon, Lorenz Wernisch:
An integrated machine learning approach for predicting DosR-regulated genes in Mycobacterium tuberculosis. BMC Systems Biology 4: 37 (2010) - Kitiporn Plaimas, Roland Eils, Rainer König:
Identifying essential genes in bacterial metabolic networks with machine learning methods. BMC Systems Biology 4: 56 (2010) - Xue Huang, Ji-Bo Wang, Li-Yan Wang, Wen-Jun Gao, Xue-Ru Wang:
Single machine scheduling with time-dependent deterioration and exponential learning effect. Computers & Industrial Engineering 58(1): 58-63 (2010) - Suh-Jenq Yang, Dar-Li Yang:
Single-machine group scheduling problems under the effects of deterioration and learning. Computers & Industrial Engineering 58(4): 754-758 (2010) - Wen-Chiung Lee, Peng-Jen Lai, Chin-Chia Wu:
Erratum to 'Single-machine and flowshop scheduling with a general learning effect model' [Computers & Industrial Engineering 56 (2009) 1553-1558]. Computers & Industrial Engineering 59(1): 181 (2010) - Dariusz Okolowski, Stanislaw Gawiejnowicz:
Exact and heuristic algorithms for parallel-machine scheduling with DeJong's learning effect. Computers & Industrial Engineering 59(2): 272-279 (2010) - Chin-Chia Wu, Chin-Liang Liu:
Minimizing the makespan on a single machine with learning and unequal release times. Computers & Industrial Engineering 59(3): 419-424 (2010) - Dan Wang, Ming-Zheng Wang, Ji-Bo Wang:
Single-machine scheduling with learning effect and resource-dependent processing times. Computers & Industrial Engineering 59(3): 458-462 (2010) - Hernane B. de B. Pereira, Gilney F. Zebende, Marcelo A. Moret:
Learning computer programming: Implementing a fractal in a Turing Machine. Computers & Education 55(2): 767-776 (2010) - Joseph MacInnes, Stephanie Santosa, William Wright:
Visual Classification: Expert Knowledge Guides Machine Learning. IEEE Computer Graphics and Applications 30(1): 8-14 (2010) - Itamar Arel, Derek Rose, Thomas P. Karnowski:
Deep Machine Learning - A New Frontier in Artificial Intelligence Research [Research Frontier]. IEEE Comp. Int. Mag. 5(4): 13-18 (2010) - Alexandra Moraru, Marko Pesko, Maria Porcius, Carolina Fortuna, Dunja Mladenic:
Using Machine Learning on Sensor Data. CIT 18(4) (2010) - Guohu Li, Min Liu, Mingyu Dong:
A new online learning algorithm for structure-adjustable extreme learning machine. Computers & Mathematics with Applications 60(3): 377-389 (2010) - Ji-Bo Wang, Ming-Zheng Wang:
Single machine multiple common due dates scheduling with learning effects. Computers & Mathematics with Applications 60(11): 2998-3002 (2010) - Daniel Voigt, Michael Döllinger, Anxiong Yang, Ulrich Eysholdt, Jörg Lohscheller:
Automatic diagnosis of vocal fold paresis by employing phonovibrogram features and machine learning methods. Computer Methods and Programs in Biomedicine 99(3): 275-288 (2010) - Jon Gillick, Kevin Tang, Robert M. Keller:
Machine Learning of Jazz Grammars. Computer Music Journal 34(3): 56-66 (2010) - Alexandros Karatzoglou, Ingo Feinerer:
Kernel-based machine learning for fast text mining in R. Computational Statistics & Data Analysis 54(2): 290-297 (2010) - Scott A. Wallace, Robert McCartney, Ingrid Russell:
Games and machine learning: a powerful combination in an artificial intelligence course. Computer Science Education 20(1): 17-36 (2010) - Jong Won Shin, Joon-Hyuk Chang, Nam Soo Kim:
Voice activity detection based on statistical models and machine learning approaches. Computer Speech & Language 24(3): 515-530 (2010) - Dursun Delen:
A comparative analysis of machine learning techniques for student retention management. Decision Support Systems 49(4): 498-506 (2010) - Sundaram Suresh, Saras Saraswathi, N. Sundararajan:
Performance enhancement of extreme learning machine for multi-category sparse data classification problems. Eng. Appl. of AI 23(7): 1149-1157 (2010) - Daniela Stojanova, Pance Panov, Valentin Gjorgjioski, Andrej Kobler, Saso Dzeroski:
Estimating vegetation height and canopy cover from remotely sensed data with machine learning. Ecological Informatics 5(4): 256-266 (2010) - Christian Kampichler, Ralf Wieland, Sophie Calmé, Holger Weissenberger, Stefan Arriaga-Weiss:
Classification in conservation biology: A comparison of five machine-learning methods. Ecological Informatics 5(6): 441-450 (2010) - Ali Faisal, Frank Dondelinger, Dirk Husmeier, Colin M. Beale:
Inferring species interaction networks from species abundance data: A comparative evaluation of various statistical and machine learning methods. Ecological Informatics 5(6): 451-464 (2010) - Kenneth Revett:
A Machine Learning Based Investigation of an Anthropometric Body Fat Dataset. Egyptian Computer Science Journal 34(5) (2010) - Nuri Firat Ince, Chu-Shu Kao, Mostafa Kaveh, Ahmed H. Tewfik, Joseph F. Labuz:
A Machine Learning Approach for Locating Acoustic Emission. EURASIP J. Adv. Sig. Proc. 2010 (2010) - Christos Koulamas:
A note on single-machine scheduling with job-dependent learning effects. European Journal of Operational Research 207(2): 1142-1143 (2010) - Kwangok Jeong, Andrew B. Kahng, B. Lin, Kambiz Samadi:
Accurate Machine-Learning-Based On-Chip Router Modeling. Embedded Systems Letters 2(3): 62-66 (2010) - Yung-Tsung Hou, Yimeng Chang, Tsuhan Chen, Chi-Sung Laih, Chia-Mei Chen:
Malicious web content detection by machine learning. Expert Syst. Appl. 37(1): 55-60 (2010) - Lean Yu, Wuyi Yue, Shouyang Wang, Kin Keung Lai:
Support vector machine based multiagent ensemble learning for credit risk evaluation. Expert Syst. Appl. 37(2): 1351-1360 (2010) - C. Deisy, S. Baskar, N. Ramaraj, J. Saravanan Koori, P. Jeevanandam:
A novel information theoretic-interact algorithm (IT-IN) for feature selection using three machine learning algorithms. Expert Syst. Appl. 37(12): 7589-7597 (2010) - V. Indira, R. Vasanthakumari, V. Sugumaran:
Minimum sample size determination of vibration signals in machine learning approach to fault diagnosis using power analysis. Expert Syst. Appl. 37(12): 8650-8658 (2010) - Federico Montesino-Pouzols, Amaury Lendasse:
Evolving fuzzy optimally pruned extreme learning machine for regression problems. Evolving Systems 1(1): 43-58 (2010) - Julián Luengo, Francisco Herrera:
Domains of competence of fuzzy rule based classification systems with data complexity measures: A case of study using a fuzzy hybrid genetic based machine learning method. Fuzzy Sets and Systems 161(1): 3-19 (2010) - Christopher J. C. Burges:
Dimension Reduction: A Guided Tour. Foundations and Trends in Machine Learning 2(4) (2010) - Stefan Steiniger, Patrick Taillandier, Robert Weibel:
Utilising urban context recognition and machine learning to improve the generalisation of buildings. International Journal of Geographical Information Science 24(2): 253-282 (2010) - Paola Mello, Sergio Storari, Bernardo Valli:
Application Of Machine Learning Techniques For The Forecasting Of Fashion Trends. Intelligenza Artificiale 4(1): 18-26 (2010) - Vasi Narasimhulu, Pothula Sujatha, P. Dhavachelvan, M. S. Saleem Basha:
Enhanced Named Entity Transliteration Model Using Machine Learning Algorithm. Int. J. Adv. Comp. Techn. 2(3): 84-93 (2010) - Ramakanta Mohanty, Vadlamani Ravi, Manas Ranjan Patra:
Application of Machine Learning Techniques to Predict Software Reliability. IJAEC 1(3): 70-86 (2010) - Jitendra Kumar Rai, Atul Negi, Rajeev Wankar, K. D. Nayak:
A Machine Learning Based Meta-Scheduler for Multi-Core Processors. IJARAS 1(4): 46-59 (2010) - Blair Howarth, Jayantha Katupitiya, Ray Eaton, Sarath Kodagoda:
A machine learning approach to crop localisation using spatial information. IJCAT 39(1/2/3): 101-108 (2010) - Kang Li, Jing Deng, Haibo He, Dajun Du:
Compact Extreme Learning Machines for biological systems. I. J. Computational Biology and Drug Design 3(2): 112-132 (2010) - Anjum Reyaz-Ahmed, Robert W. Harrison, Yan-Qing Zhang:
Protein model assessment via machine learning techniques. I. J. Functional Informatics and Personalised Medicine 3(3): 215-227 (2010) - C. Ugwu, N. Onyejegbu, I. C. Obagbuwa:
The Application of Machine Learning Technique for Malaria Diagnosis. IJGC 1(1): 68-77 (2010) - Xingwei Wang, Dror Lederman, Jun Tan, Bin Zheng:
Computer-aided Detection: The Impact of Machine Learning Classifier and Image Feature Selection on Scheme Performance. IJIIP 1(1): 30-40 (2010) - Sean Duignan, Tony Hall:
From virtual machines to actual systems - realising the potential of virtualisation technologies for teaching, learning, and assessment in 'computing' education. IJLT 5(1): 25-41 (2010) - Jiuwen Cao, Zhiping Lin, Guang-Bin Huang:
Composite function wavelet neural networks with extreme learning machine. Neurocomputing 73(7-9): 1405-1416 (2010) - Matteo Re, Giorgio Valentini:
Integration of heterogeneous data sources for gene function prediction using decision templates and ensembles of learning machines. Neurocomputing 73(7-9): 1533-1537 (2010) - Rashid Minhas, Abdul Adeel Mohammed, Q. M. Jonathan Wu:
A fast recognition framework based on extreme learning machine using hybrid object information. Neurocomputing 73(10-12): 1831-1839 (2010) - Rashid Minhas, Aryaz Baradarani, Sepideh Seifzadeh, Q. M. Jonathan Wu:
Human action recognition using extreme learning machine based on visual vocabularies. Neurocomputing 73(10-12): 1906-1917 (2010) - V. Malathi, N. S. Marimuthu, S. Baskar:
Intelligent approaches using support vector machine and extreme learning machine for transmission line protection. Neurocomputing 73(10-12): 2160-2167 (2010) - Ting Yu, Simeon J. Simoff, Tony Jan:
VQSVM: A case study for incorporating prior domain knowledge into inductive machine learning. Neurocomputing 73(13-15): 2614-2623 (2010) - Yuan Lan, Yeng Chai Soh, Guang-Bin Huang:
Two-stage extreme learning machine for regression. Neurocomputing 73(16-18): 3028-3038 (2010) - Yuan Lan, Yeng Chai Soh, Guang-Bin Huang:
Constructive hidden nodes selection of extreme learning machine for regression. Neurocomputing 73(16-18): 3191-3199 (2010) - Guang-Bin Huang, Xiaojian Ding, Hongming Zhou:
Optimization method based extreme learning machine for classification. Neurocomputing 74(1-3): 155-163 (2010) - Wanyu Deng, Qinghua Zheng, Shiguo Lian, Lin Chen, Xin Wang:
Ordinal extreme learning machine. Neurocomputing 74(1-3): 447-456 (2010) - Jianwen Tao, Shitong Wang, Wenjun Hu, Wenhao Ying:
p-Margin Kernel Learning Machine with Magnetic Field Effect for Both Binary Classification and Novelty Detection. Int. J. Software and Informatics 4(3): 305-324 (2010) - Kensuke Naoe, Hideyasu Sasaki, Yoshiyasu Takefuji:
Secure Key Generation for Static Visual Watermarking by Machine Learning in Intelligent Systems and Services. IJSSOE 1(1): 46-61 (2010) - Zou Peng, Yuanyuan Hao, Yijun Li:
Customer value segmentation based on cost-sensitive learning Support Vector Machine. IJSTM 14(1): 126-137 (2010) - Adriano L. I. Oliveira, Petrônio L. Braga, Ricardo Massa Ferreira Lima, Márcio Cornélio:
GA-based method for feature selection and parameters optimization for machine learning regression applied to software effort estimation. Information & Software Technology 52(11): 1155-1166 (2010) - Wen-Chiung Lee, Peng-Jen Lai, Chin-Chia Wu:
Erratum to 'Some single-machine and m-machine flowshop scheduling problems with learning considerations' [Inform. Sci. 179(2009) 3885-3892]. Inf. Sci. 180(6): 1073 (2010) - Wen-Hung Kuo, Dar-Li Yang:
Note on "Single-machine and flowshop scheduling with a general learning effect model" and "Some single-machine and m-machine flowshop scheduling problems with learning considerations". Inf. Sci. 180(19): 3814-3816 (2010) - Ruixi Yuan, Zhu Li, Xiaohong Guan, Li Xu:
An SVM-based machine learning method for accurate internet traffic classification. Information Systems Frontiers 12(2): 149-156 (2010) - Bogdan Raducanu, Jordi Vitrià, Ales Leonardis:
Online pattern recognition and machine learning techniques for computer-vision: Theory and applications. Image Vision Comput. 28(7): 1063-1064 (2010) - Eraldo R. Fernandes, Ruy Luiz Milidiú, Raúl P. Rentería:
RelHunter: a machine learning method for relation extraction from text. J. Braz. Comp. Soc. 16(3): 191-199 (2010) - Roxana Dánger, Isabel Segura-Bedmar, Paloma Martínez Fernández, Paolo Rosso:
A comparison of machine learning techniques for detection of drug target articles. Journal of Biomedical Informatics 43(6): 902-913 (2010) - M. F. López, José M. Martínez, José M. Matías, Javier Taboada, José A. Vilán:
Functional classification of ornamental stone using machine learning techniques. J. Computational Applied Mathematics 234(4): 1338-1345 (2010) - M. F. López, J. Martínez, José M. Matías, Javier Taboada, José A. Vilán:
Shape functional optimization with restrictions boosted with machine learning techniques. J. Computational Applied Mathematics 234(8): 2609-2615 (2010) - Xue-Gang Yang, Wei Lv, Yu Zong Chen, Ying Xue:
In silico prediction and screening of gamma-secretase inhibitors by molecular descriptors and machine learning methods. Journal of Computational Chemistry 31(6): 1249-1258 (2010) - Nikolas Fechner, Andreas Jahn, Georg Hinselmann, Andreas Zell:
Estimation of the applicability domain of kernel-based machine learning models for virtual screening. J. Cheminformatics 2: 2 (2010) - Tomohiro Sato, Teruki Honma, Shigeyuki Yokoyama:
Combining Machine Learning and Pharmacophore-Based Interaction Fingerprint for in Silico Screening. Journal of Chemical Information and Modeling 50(1): 170-185 (2010) - Shivani Agarwal, Deepak Dugar, Shiladitya Sengupta:
Ranking Chemical Structures for Drug Discovery: A New Machine Learning Approach. Journal of Chemical Information and Modeling 50(5): 716-731 (2010) - Yevgeniy Podolyan, Michael A. Walters, George Karypis:
Assessing Synthetic Accessibility of Chemical Compounds Using Machine Learning Methods. Journal of Chemical Information and Modeling 50(6): 979-991 (2010) - Chris Drummond, Nathalie Japkowicz:
Warning: statistical benchmarking is addictive. Kicking the habit in machine learning. J. Exp. Theor. Artif. Intell. 22(1): 67-80 (2010) - Lei Xu:
Machine learning problems from optimization perspective. J. Global Optimization 47(3): 369-401 (2010) - V. Mallika, K. C. Sivakumar, S. Jaichand, E. V. Soniya:
Kernel based machine learning algorithm for the efficient prediction of type III polyketide synthase family of proteins. J. Integrative Bioinformatics 7(1) (2010) - Sridhar Dutta, Sukumar Bandopadhyay, Rajive Ganguli, Debasmita Misra:
Machine Learning Algorithms and Their Application to Ore Reserve Estimation of Sparse and Imprecise Data. JILSA 2(2): 86-96 (2010) - M. Duran Toksari, Ertan Güner:
Parallel machine scheduling problem to minimize the earliness/tardiness costs with learning effect and deteriorating jobs. J. Intelligent Manufacturing 21(6): 843-851 (2010) - Erik Strumbelj, Igor Kononenko:
An Efficient Explanation of Individual Classifications using Game Theory. Journal of Machine Learning Research 11: 1-18 (2010) - Julien Mairal, Francis R. Bach, Jean Ponce, Guillermo Sapiro:
Online Learning for Matrix Factorization and Sparse Coding. Journal of Machine Learning Research 11: 19-60 (2010) - Isabelle Guyon, Amir Saffari, Gideon Dror, Gavin C. Cawley:
Model Selection: Beyond the Bayesian/Frequentist Divide. Journal of Machine Learning Research 11: 61-87 (2010) - András György, Gábor Lugosi, György Ottucsák:
On-Line Sequential Bin Packing. Journal of Machine Learning Research 11: 89-109 (2010) - Ming Yuan, Marten H. Wegkamp:
Classification Methods with Reject Option Based on Convex Risk Minimization. Journal of Machine Learning Research 11: 111-130 (2010) - Yufeng Ding, Jeffrey S. Simonoff:
An Investigation of Missing Data Methods for Classification Trees Applied to Binary Response Data. Journal of Machine Learning Research 11: 131-170 (2010) - Constantin F. Aliferis, Alexander R. Statnikov, Ioannis Tsamardinos, Subramani Mani, Xenofon D. Koutsoukos:
Local Causal and Markov Blanket Induction for Causal Discovery and Feature Selection for Classification Part I: Algorithms and Empirical Evaluation. Journal of Machine Learning Research 11: 171-234 (2010) - Constantin F. Aliferis, Alexander R. Statnikov, Ioannis Tsamardinos, Subramani Mani, Xenofon D. Koutsoukos:
Local Causal and Markov Blanket Induction for Causal Discovery and Feature Selection for Classification Part II: Analysis and Extensions. Journal of Machine Learning Research 11: 235-284 (2010) - Kaname Kojima, Eric Perrier, Seiya Imoto, Satoru Miyano:
Optimal Search on Clustered Structural Constraint for Learning Bayesian Network Structure. Journal of Machine Learning Research 11: 285-310 (2010) - Choon Hui Teo, S. V. N. Vishwanathan, Alexander J. Smola, Quoc V. Le:
Bundle Methods for Regularized Risk Minimization. Journal of Machine Learning Research 11: 311-365 (2010) - Dotan Di Castro, Ron Meir:
A Convergent Online Single Time Scale Actor Critic Algorithm. Journal of Machine Learning Research 11: 367-410 (2010) - Philippos Mordohai, Gérard G. Medioni:
Dimensionality Estimation, Manifold Learning and Function Approximation using Tensor Voting. Journal of Machine Learning Research 11: 411-450 (2010) - Jarkko Venna, Jaakko Peltonen, Kristian Nybo, Helena Aidos, Samuel Kaski:
Information Retrieval Perspective to Nonlinear Dimensionality Reduction for Data Visualization. Journal of Machine Learning Research 11: 451-490 (2010) - Kush R. Varshney, Alan S. Willsky:
Classification Using Geometric Level Sets. Journal of Machine Learning Research 11: 491-516 (2010) - Michel Journée, Yurii Nesterov, Peter Richtárik, Rodolphe Sepulchre:
Generalized Power Method for Sparse Principal Component Analysis. Journal of Machine Learning Research 11: 517-553 (2010) - Konrad Rieck, Tammo Krueger, Ulf Brefeld, Klaus-Robert Müller:
Approximate Tree Kernels. Journal of Machine Learning Research 11: 555-580 (2010) - Daniil Ryabko:
On Finding Predictors for Arbitrary Families of Processes. Journal of Machine Learning Research 11: 581-602 (2010) - Patrick O. Perry, Art B. Owen:
A Rotation Test to Verify Latent Structure. Journal of Machine Learning Research 11: 603-624 (2010) - Dumitru Erhan, Yoshua Bengio, Aaron C. Courville, Pierre-Antoine Manzagol, Pascal Vincent, Samy Bengio:
Why Does Unsupervised Pre-training Help Deep Learning? Journal of Machine Learning Research 11: 625-660 (2010) - Sergio Escalera, Oriol Pujol, Petia Radeva:
Error-Correcting Ouput Codes Library. Journal of Machine Learning Research 11: 661-664 (2010) - Christoforos Christoforou, Robert M. Haralick, Paul Sajda, Lucas C. Parra:
Second-Order Bilinear Discriminant Analysis. Journal of Machine Learning Research 11: 665-685 (2010) - Gérard Biau, Frédéric Cérou, Arnaud Guyader:
On the Rate of Convergence of the Bagged Nearest Neighbor Estimate. Journal of Machine Learning Research 11: 687-712 (2010) - Jianing Shi, Wotao Yin, Stanley Osher, Paul Sajda:
A Fast Hybrid Algorithm for Large-Scale l1-Regularized Logistic Regression. Journal of Machine Learning Research 11: 713-741 (2010) - Tom Schaul, Justin Bayer, Daan Wierstra, Yi Sun, Martin Felder, Frank Sehnke, Thomas Rückstieß, Jürgen Schmidhuber:
PyBrain. Journal of Machine Learning Research 11: 743-746 (2010) - Pannagadatta K. Shivaswamy, Tony Jebara:
Maximum Relative Margin and Data-Dependent Regularization. Journal of Machine Learning Research 11: 747-788 (2010) - Mehryar Mohri, Afshin Rostamizadeh:
Stability Bounds for Stationary phi-mixing and beta-mixing Processes. Journal of Machine Learning Research 11: 789-814 (2010) - Fang-Lan Huang, Cho-Jui Hsieh, Kai-Wei Chang, Chih-Jen Lin:
Iterative Scaling and Coordinate Descent Methods for Maximum Entropy Models. Journal of Machine Learning Research 11: 815-848 (2010) - Yael Ben-Haim, Elad Tom-Tov:
A Streaming Parallel Decision Tree Algorithm. Journal of Machine Learning Research 11: 849-872 (2010) - Valero Laparra, Jaime Gutierrez, Gustavo Camps-Valls, Jesús Malo:
Image Denoising with Kernels Based on Natural Image Relations. Journal of Machine Learning Research 11: 873-903 (2010) - Lorenzo Rosasco, Mikhail Belkin, Ernesto De Vito:
On Learning with Integral Operators. Journal of Machine Learning Research 11: 905-934 (2010) - Andreas Argyriou, Charles A. Micchelli, Massimiliano Pontil:
On Spectral Learning. Journal of Machine Learning Research 11: 935-953 (2010) - Gideon S. Mann, Andrew McCallum:
Generalized Expectation Criteria for Semi-Supervised Learning with Weakly Labeled Data. Journal of Machine Learning Research 11: 955-984 (2010) - Jure Leskovec, Deepayan Chakrabarti, Jon M. Kleinberg, Christos Faloutsos, Zoubin Ghahramani:
Kronecker Graphs: An Approach to Modeling Networks. Journal of Machine Learning Research 11: 985-1042 (2010) - Pradeep D. Ravikumar, Alekh Agarwal, Martin J. Wainwright:
Message-passing for Graph-structured Linear Programs: Proximal Methods and Rounding Schemes. Journal of Machine Learning Research 11: 1043-1080 (2010) - Tong Zhang:
Analysis of Multi-stage Convex Relaxation for Sparse Regularization. Journal of Machine Learning Research 11: 1081-1107 (2010) - Gal Chechik, Varun Sharma, Uri Shalit, Samy Bengio:
Large Scale Online Learning of Image Similarity Through Ranking. Journal of Machine Learning Research 11: 1109-1135 (2010) - Christian R. Shelton, Yu Fan, William Lam, Joon Lee, Jing Xu:
Continuous Time Bayesian Network Reasoning and Learning Engine. Journal of Machine Learning Research 11: 1137-1140 (2010) - Andreas Krause:
SFO: A Toolbox for Submodular Function Optimization. Journal of Machine Learning Research 11: 1141-1144 (2010) - Jin Yu, S. V. N. Vishwanathan, Simon Günter, Nicol N. Schraudolph:
A Quasi-Newton Approach to Nonsmooth Convex Optimization Problems in Machine Learning. Journal of Machine Learning Research 11: 1145-1200 (2010) - S. V. N. Vishwanathan, Nicol N. Schraudolph, Risi Kondor, Karsten M. Borgwardt:
Graph Kernels. Journal of Machine Learning Research 11: 1201-1242 (2010) - Miki Aoyagi:
Stochastic Complexity and Generalization Error of a Restricted Boltzmann Machine in Bayesian Estimation. Journal of Machine Learning Research 11: 1243-1272 (2010) - Vicenç Gómez, Hilbert J. Kappen, Michael Chertkov:
Approximate Inference on Planar Graphs using Loop Calculus and Belief Propagation. Journal of Machine Learning Research 11: 1273-1296 (2010) - Vikas C. Raykar, Shipeng Yu, Linda H. Zhao, Gerardo Hermosillo Valadez, Charles Florin, Luca Bogoni, Linda Moy:
Learning From Crowds. Journal of Machine Learning Research 11: 1297-1322 (2010) - Pinar Donmez, Guy Lebanon, Krishnakumar Balasubramanian:
Unsupervised Supervised Learning I: Estimating Classification and Regression Errors without Labels. Journal of Machine Learning Research 11: 1323-1351 (2010) - Sayed Kamaledin Ghiasi Shirazi, Reza Safabakhsh, Mostafa Shamsi:
Learning Translation Invariant Kernels for Classification. Journal of Machine Learning Research 11: 1353-1390 (2010) - Arthur Gretton, László Györfi:
Consistent Nonparametric Tests of Independence. Journal of Machine Learning Research 11: 1391-1423 (2010) - Gunnar E. Carlsson, Facundo Mémoli:
Characterization, Stability and Convergence of Hierarchical Clustering Methods. Journal of Machine Learning Research 11: 1425-1470 (2010) - Yin-Wen Chang, Cho-Jui Hsieh, Kai-Wei Chang, Michael Ringgaard, Chih-Jen Lin:
Training and Testing Low-degree Polynomial Data Mappings via Linear SVM. Journal of Machine Learning Research 11: 1471-1490 (2010) - Irene Rodriguez-Lujan, Ramón Huerta, Charles Elkan, Carlos Santa Cruz:
Quadratic Programming Feature Selection. Journal of Machine Learning Research 11: 1491-1516 (2010) - Bharath K. Sriperumbudur, Arthur Gretton, Kenji Fukumizu, Bernhard Schölkopf, Gert R. G. Lanckriet:
Hilbert Space Embeddings and Metrics on Probability Measures. Journal of Machine Learning Research 11: 1517-1561 (2010) - Thomas Jaksch, Ronald Ortner, Peter Auer:
Near-optimal Regret Bounds for Reinforcement Learning. Journal of Machine Learning Research 11: 1563-1600 (2010) - Albert Bifet, Geoff Holmes, Richard Kirkby, Bernhard Pfahringer:
MOA: Massive Online Analysis. Journal of Machine Learning Research 11: 1601-1604 (2010) - Ran El-Yaniv, Yair Wiener:
On the Foundations of Noise-free Selective Classification. Journal of Machine Learning Research 11: 1605-1641 (2010) - Peter Spirtes:
Introduction to Causal Inference. Journal of Machine Learning Research 11: 1643-1662 (2010) - Pedro A. Forero, Alfonso Cano, Georgios B. Giannakis:
Consensus-Based Distributed Support Vector Machines. Journal of Machine Learning Research 11: 1663-1707 (2010) - Aapo Hyvärinen, Kun Zhang, Shohei Shimizu, Patrik O. Hoyer:
Estimation of a Structural Vector Autoregression Model Using Non-Gaussianity. Journal of Machine Learning Research 11: 1709-1731 (2010) - Ariel Jaimovich, Ofer Meshi, Ian McGraw, Gal Elidan:
FastInf: An Efficient Approximate Inference Library. Journal of Machine Learning Research 11: 1733-1736 (2010) - Phillip Verbancsics, Kenneth O. Stanley:
Evolving Static Representations for Task Transfer. Journal of Machine Learning Research 11: 1737-1769 (2010) - Ryo Yoshida, Mike West:
Bayesian Learning in Sparse Graphical Factor Models via Variational Mean-Field Annealing. Journal of Machine Learning Research 11: 1771-1798 (2010) - Sören Sonnenburg, Gunnar Rätsch, Sebastian Henschel, Christian Widmer, Jonas Behr, Alexander Zien, Fabio De Bona, Alexander Binder, Christian Gehl, Vojtech Franc:
The SHOGUN Machine Learning Toolbox. Journal of Machine Learning Research 11: 1799-1802 (2010) - David Baehrens, Timon Schroeter, Stefan Harmeling, Motoaki Kawanabe, Katja Hansen, Klaus-Robert Müller:
How to Explain Individual Classification Decisions. Journal of Machine Learning Research 11: 1803-1831 (2010) - Markus Ojala, Gemma C. Garriga:
Permutation Tests for Studying Classifier Performance. Journal of Machine Learning Research 11: 1833-1863 (2010) - Miguel Lázaro-Gredilla, Joaquin Quiñonero Candela, Carl Edward Rasmussen, Aníbal R. Figueiras-Vidal:
Sparse Spectrum Gaussian Process Regression. Journal of Machine Learning Research 11: 1865-1881 (2010) - Nicola Segata, Enrico Blanzieri:
Fast and Scalable Local Kernel Machines. Journal of Machine Learning Research 11: 1883-1926 (2010) - Liva Ralaivola, Marie Szafranski, Guillaume Stempfel:
Chromatic PAC-Bayes Bounds for Non-IID Data: Applications to Ranking and Stationary β-Mixing Processes. Journal of Machine Learning Research 11: 1927-1956 (2010) - Alexander Ilin, Tapani Raiko:
Practical Approaches to Principal Component Analysis in the Presence of Missing Values. Journal of Machine Learning Research 11: 1957-2000 (2010) - Kuzman Ganchev, João Graça, Jennifer Gillenwater, Ben Taskar:
Posterior Regularization for Structured Latent Variable Models. Journal of Machine Learning Research 11: 2001-2049 (2010) - Dirk Gorissen, Ivo Couckuyt, Piet Demeester, Tom Dhaene, Karel Crombecq:
A Surrogate Modeling and Adaptive Sampling Toolbox for Computer Based Design. Journal of Machine Learning Research 11: 2051-2055 (2010) - Raghunandan H. Keshavan, Andrea Montanari, Sewoong Oh:
Matrix Completion from Noisy Entries. Journal of Machine Learning Research 11: 2057-2078 (2010) - Gavin C. Cawley, Nicola L. C. Talbot:
On Over-fitting in Model Selection and Subsequent Selection Bias in Performance Evaluation. Journal of Machine Learning Research 11: 2079-2107 (2010) - Torsten Hothorn, Peter Bühlmann, Thomas Kneib, Matthias Schmid, Benjamin Hofner:
Model-based Boosting 2.0. Journal of Machine Learning Research 11: 2109-2113 (2010) - Yu Fan, Jing Xu, Christian R. Shelton:
Importance Sampling for Continuous Time Bayesian Networks. Journal of Machine Learning Research 11: 2115-2140 (2010) - Guoqiang Yu, Yuanjian Feng, David J. Miller, Jianhua Xuan, Eric P. Hoffman, Robert Clarke, Ben Davidson, Ie-Ming Shih, Yue Joseph Wang:
Matched Gene Selection and Committee Classifier for Molecular Classification of Heterogeneous Diseases. Journal of Machine Learning Research 11: 2141-2167 (2010) - Joris M. Mooij:
libDAI: A Free and Open Source C++ Library for Discrete Approximate Inference in Graphical Models. Journal of Machine Learning Research 11: 2169-2173 (2010) - Qiang Wu, Justin Guinney, Mauro Maggioni, Sayan Mukherjee:
Learning Gradients: Predictive Models that Infer Geometry and Statistical Dependence. Journal of Machine Learning Research 11: 2175-2198 (2010) - Zhihua Zhang, Guang Dai, Congfu Xu, Michael I. Jordan:
Regularized Discriminant Analysis, Ridge Regression and Beyond. Journal of Machine Learning Research 11: 2199-2228 (2010) - Antoine Bordes, Léon Bottou, Patrick Gallinari, Jonathan Chang, S. Alex Smith:
Erratum: SGDQN is Less Careful than Expected. Journal of Machine Learning Research 11: 2229-2240 (2010) - Garvesh Raskutti, Martin J. Wainwright, Bin Yu:
Restricted Eigenvalue Properties for Correlated Gaussian Designs. Journal of Machine Learning Research 11: 2241-2259 (2010) - Ming Yuan:
High Dimensional Inverse Covariance Matrix Estimation via Linear Programming. Journal of Machine Learning Research 11: 2261-2286 (2010) - Rahul Mazumder, Trevor Hastie, Robert Tibshirani:
Spectral Regularization Algorithms for Learning Large Incomplete Matrices. Journal of Machine Learning Research 11: 2287-2322 (2010) - Franz Pernkopf, Jeff A. Bilmes:
Efficient Heuristics for Discriminative Structure Learning of Bayesian Network Classifiers. Journal of Machine Learning Research 11: 2323-2360 (2010) - Dapo Omidiran, Martin J. Wainwright:
High-dimensional Variable Selection with Sparse Random Projections: Measurement Sparsity and Statistical Efficiency. Journal of Machine Learning Research 11: 2361-2386 (2010) - Mark D. Reid, Robert C. Williamson:
Composite Binary Losses. Journal of Machine Learning Research 11: 2387-2422 (2010) - Shiliang Sun, John Shawe-Taylor:
Sparse Semi-supervised Learning Using Conjugate Functions. Journal of Machine Learning Research 11: 2423-2455 (2010) - Vladimir Koltchinskii:
Rademacher Complexities and Bounding the Excess Risk in Active Learning. Journal of Machine Learning Research 11: 2457-2485 (2010) - Milos Radovanovic, Alexandros Nanopoulos, Mirjana Ivanovic:
Hubs in Space: Popular Nearest Neighbors in High-Dimensional Data. Journal of Machine Learning Research 11: 2487-2531 (2010) - Remco R. Bouckaert, Eibe Frank, Mark A. Hall, Geoffrey Holmes, Bernhard Pfahringer, Peter Reutemann, Ian H. Witten:
WEKA - Experiences with a Java Open-Source Project. Journal of Machine Learning Research 11: 2533-2541 (2010) - Lin Xiao:
Dual Averaging Methods for Regularized Stochastic Learning and Online Optimization. Journal of Machine Learning Research 11: 2543-2596 (2010) - Joshua V. Dillon, Guy Lebanon:
Stochastic Composite Likelihood. Journal of Machine Learning Research 11: 2597-2633 (2010) - Shai Shalev-Shwartz, Ohad Shamir, Nathan Srebro, Karthik Sridharan:
Learnability, Stability and Uniform Convergence. Journal of Machine Learning Research 11: 2635-2670 (2010) - Jitkomut Songsiri, Lieven Vandenberghe:
Topology Selection in Graphical Models of Autoregressive Processes. Journal of Machine Learning Research 11: 2671-2705 (2010) - Alexander Clark, Rémi Eyraud, Amaury Habrard:
Using Contextual Representations to Efficiently Learn Context-Free Languages. Journal of Machine Learning Research 11: 2707-2744 (2010) - Ido Cohn, Tal El-Hay, Nir Friedman, Raz Kupferman:
Mean Field Variational Approximation for Continuous-Time Bayesian Networks. Journal of Machine Learning Research 11: 2745-2783 (2010) - Jean-Yves Audibert, Sébastien Bubeck:
Regret Bounds and Minimax Policies under Partial Monitoring. Journal of Machine Learning Research 11: 2785-2836 (2010) - Xuan Vinh Nguyen, Julien Epps, James Bailey:
Information Theoretic Measures for Clusterings Comparison: Variants, Properties, Normalization and Correction for Chance. Journal of Machine Learning Research 11: 2837-2854 (2010) - Jörg Lücke, Julian Eggert:
Expectation Truncation and the Benefits of Preselection In Training Generative Models. Journal of Machine Learning Research 11: 2855-2900 (2010) - Giovanni Cavallanti, Nicolò Cesa-Bianchi, Claudio Gentile:
Linear Algorithms for Online Multitask Classification. Journal of Machine Learning Research 11: 2901-2934 (2010) - Fu Chang, Chien-Yang Guo, Xiao-Rong Lin, Chi-Jen Lu:
Tree Decomposition for Large-Scale SVM Problems. Journal of Machine Learning Research 11: 2935-2972 (2010) - Gilles Blanchard, Gyemin Lee, Clayton Scott:
Semi-Supervised Novelty Detection. Journal of Machine Learning Research 11: 2973-3009 (2010) - Carl Edward Rasmussen, Hannes Nickisch:
Gaussian Processes for Machine Learning (GPML) Toolbox. Journal of Machine Learning Research 11: 3011-3015 (2010) - Shay B. Cohen, Noah A. Smith:
Covariance in Unsupervised Learning of Probabilistic Grammars. Journal of Machine Learning Research 11: 3017-3051 (2010) - Trevor Cohn, Phil Blunsom, Sharon Goldwater:
Inducing Tree-Substitution Grammars. Journal of Machine Learning Research 11: 3053-3096 (2010) - Rahul Gupta, Sunita Sarawagi, Ajit A. Diwan:
Collective Inference for Extraction MRFs Coupled with Symmetric Clique Potentials. Journal of Machine Learning Research 11: 3097-3135 (2010) - Evangelos Theodorou, Jonas Buchli, Stefan Schaal:
A Generalized Path Integral Control Approach to Reinforcement Learning. Journal of Machine Learning Research 11: 3137-3181 (2010) - Guo-Xun Yuan, Kai-Wei Chang, Cho-Jui Hsieh, Chih-Jen Lin:
A Comparison of Optimization Methods and Software for Large-scale L1-regularized Linear Classification. Journal of Machine Learning Research 11: 3183-3234 (2010) - Antti Honkela, Tapani Raiko, Mikael Kuusela, Matti Tornio, Juha Karhunen:
Approximate Riemannian Conjugate Gradient Learning for Fixed-Form Variational Bayes. Journal of Machine Learning Research 11: 3235-3268 (2010) - Chunping Wang, Xuejun Liao, Lawrence Carin, David B. Dunson:
Classification with Incomplete Data Using Dirichlet Process Priors. Journal of Machine Learning Research 11: 3269-3311 (2010) - Jacek P. Dmochowski, Paul Sajda, Lucas C. Parra:
Maximum Likelihood in Cost-Sensitive Learning: Model Specification, Approximations, and Upper Bounds. Journal of Machine Learning Research 11: 3313-3332 (2010) - Shyam Visweswaran, Gregory F. Cooper:
Learning Instance-Specific Predictive Models. Journal of Machine Learning Research 11: 3333-3369 (2010) - Pascal Vincent, Hugo Larochelle, Isabelle Lajoie, Yoshua Bengio, Pierre-Antoine Manzagol:
Stacked Denoising Autoencoders: Learning Useful Representations in a Deep Network with a Local Denoising Criterion. Journal of Machine Learning Research 11: 3371-3408 (2010) - Fabian H. Sinz, Matthias Bethge:
Lp-Nested Symmetric Distributions. Journal of Machine Learning Research 11: 3409-3451 (2010) - Remco R. Bouckaert, Raymond Hemmecke, Silvia Lindner, Milan Studený:
Efficient Algorithms for Conditional Independence Inference. Journal of Machine Learning Research 11: 3453-3479 (2010) - Marina Meila, Le Bao:
An Exponential Model for Infinite Rankings. Journal of Machine Learning Research 11: 3481-3518 (2010) - Fei Ye, Cun-Hui Zhang:
Rate Minimaxity of the Lasso and Dantzig Selector for the lq Loss in lr Balls. Journal of Machine Learning Research 11: 3519-3540 (2010) - James Henderson, Ivan Titov:
Incremental Sigmoid Belief Networks for Grammar Learning. Journal of Machine Learning Research 11: 3541-3570 (2010) - Sumio Watanabe:
Asymptotic Equivalence of Bayes Cross Validation and Widely Applicable Information Criterion in Singular Learning Theory. Journal of Machine Learning Research 11: 3571-3594 (2010) - Yevgeny Seldin, Naftali Tishby:
PAC-Bayesian Analysis of Co-clustering and Beyond. Journal of Machine Learning Research 11: 3595-3646 (2010) - Joshua W. Robinson, Alexander J. Hartemink:
Learning Non-Stationary Dynamic Bayesian Networks. Journal of Machine Learning Research 11: 3647-3680 (2010) - Ryan Lichtenwalter, Katerina Lichtenwalter, Nitesh V. Chawla:
A Machine-Learning Approach to Autonomous Music Composition. J. Intelligent Systems 19(2): 95-124 (2010) - J.-B. Wang:
Single-machine scheduling with a sum-of-actual-processing-time-based learning effect. JORS 61(1): 172-177 (2010) - W.-H. Kuo, D.-L. Yang:
Single-machine scheduling with a sum-of-actual-processing-time-based learning effect. JORS 61(2): 352-355 (2010) - J.-B. Wang:
Response to Viewpoint on 'Single-machine with a sum-of-actual-processing-time-based learning effect'. JORS 61(2): 355 (2010) - Tse-Wei Chen, Chi-Sun Tang, Sung-Fang Tsai, Chen-Han Tsai, Shao-Yi Chien, Liang-Gee Chen:
Tera-Scale Performance Machine Learning SoC (MLSoC) With Dual Stream Processor Architecture for Multimedia Content Analysis. J. Solid-State Circuits 45(11): 2321-2329 (2010) - Vikramjit Mitra, Hosung Nam, Carol Y. Espy-Wilson, Elliot Saltzman, Louis Goldstein:
Retrieving Tract Variables From Acoustics: A Comparison of Different Machine Learning Strategies. J. Sel. Topics Signal Processing 4(6): 1027-1045 (2010) - Xiaoliang Tang, Min Han:
Ternary reversible extreme learning machines: the incremental tri-training method for semi-supervised classification. Knowl. Inf. Syst. 23(3): 345-372 (2010) - Simon Parsons:
Introduction to Machine Learning, Second Editon by Ethem Alpaydin, MIT Press, 584 pp., ISBN 978-0-262-01243-0. Knowledge Eng. Review 25(3): 353 (2010) - Matthew L. Jockers, Daniela M. Witten:
A comparative study of machine learning methods for authorship attribution. LLC 25(2): 215-223 (2010) - Xingong Zhang, Guangle Yan:
Machine scheduling problems with a general learning effect. Mathematical and Computer Modelling 51(1-2): 84-90 (2010) - Wen-Hung Kuo, Dar-Li Yang:
Erratum to: "Machine scheduling with a general learning effect" [Math. Comput. Modelling 51(1-2) (2010) 84-90]. Mathematical and Computer Modelling 51(5-6): 847-849 (2010) - David Corfield:
Varieties of Justification in Machine Learning. Minds and Machines 20(2): 291-301 (2010) - José L. Balcázar, Albert Bifet, Antoni Lozano:
Mining frequent closed rooted trees. Machine Learning 78(1-2): 1-33 (2010) - Masashi Sugiyama, Tsuyoshi Idé, Shinichi Nakajima, Jun Sese:
Semi-supervised local Fisher discriminant analysis for dimensionality reduction. Machine Learning 78(1-2): 35-61 (2010) - Manfred K. Warmuth, Dima Kuzmin:
Bayesian generalized probability calculus for density matrices. Machine Learning 78(1-2): 63-101 (2010) - Charles Dugas, David Gadoury:
Pointwise exact bootstrap distributions of ROC curves. Machine Learning 78(1-2): 103-136 (2010) - Isaac Martín de Diego, Alberto Muñoz, Javier M. Moguerza:
Methods for the combination of kernel matrices within a support vector framework. Machine Learning 78(1-2): 137-174 (2010) - François Laviolette, Mario Marchand, Mohak Shah, Sara Shanian:
Learning the set covering machine by bound minimization and margin-sparsity trade-off. Machine Learning 78(1-2): 175-201 (2010) - Jens Lehmann, Pascal Hitzler:
Concept learning in description logics using refinement operators. Machine Learning 78(1-2): 203-250 (2010) - Daan Fierens, Jan Ramon, Hendrik Blockeel, Maurice Bruynooghe:
A comparison of pruning criteria for probability trees. Machine Learning 78(1-2): 251-285 (2010) - Philip M. Long, Rocco A. Servedio:
Random classification noise defeats all convex potential boosters. Machine Learning 78(3): 287-304 (2010) - Niels Landwehr, Andrea Passerini, Luc De Raedt, Paolo Frasconi:
Fast learning of relational kernels. Machine Learning 78(3): 305-342 (2010) - Frederik Janssen, Johannes Fürnkranz:
On the quest for optimal rule learning heuristics. Machine Learning 78(3): 343-379 (2010) - Nicolás García-Pedrajas, Juan Antonio Romero del Castillo, Domingo Ortiz-Boyer:
A cooperative coevolutionary algorithm for instance selection for instance-based learning. Machine Learning 78(3): 381-420 (2010) - Janez Demsar:
Algorithms for subsetting attribute values with Relief. Machine Learning 78(3): 421-428 (2010) - Nicolò Cesa-Bianchi, David R. Hardoon, Gayle Leen:
Guest Editorial: Learning from multiple sources. Machine Learning 79(1-2): 1-3 (2010) - Felix Bießmann, Frank C. Meinecke, Arthur Gretton, Alexander Rauch, Gregor Rainer, Nikos K. Logothetis, Klaus-Robert Müller:
Temporal kernel CCA and its application in multimodal neuronal data analysis. Machine Learning 79(1-2): 5-27 (2010) - David R. Hardoon, John Shawe-Taylor:
Decomposing the tensor kernel support vector machine for neuroscience data with structured labels. Machine Learning 79(1-2): 29-46 (2010) - Virginia R. de Sa, Patrick W. Gallagher, Joshua M. Lewis, Vicente L. Malave:
Multi-view kernel construction. Machine Learning 79(1-2): 47-71 (2010) - Marie Szafranski, Yves Grandvalet, Alain Rakotomamonjy:
Composite kernel learning. Machine Learning 79(1-2): 73-103 (2010) - Massih-Reza Amini, Cyril Goutte:
A co-classification approach to learning from multilingual corpora. Machine Learning 79(1-2): 105-121 (2010) - Mark Dredze, Alex Kulesza, Koby Crammer:
Multi-domain learning by confidence-weighted parameter combination. Machine Learning 79(1-2): 123-149 (2010) - Shai Ben-David, John Blitzer, Koby Crammer, Alex Kulesza, Fernando Pereira, Jennifer Wortman Vaughan:
A theory of learning from different domains. Machine Learning 79(1-2): 151-175 (2010) - Vikas Singh, Lopamudra Mukherjee, Jiming Peng, Jinhui Xu:
Ensemble clustering using semidefinite programming with applications. Machine Learning 79(1-2): 177-200 (2010) - Simon Rogers, Arto Klami, Janne Sinkkonen, Mark Girolami, Samuel Kaski:
Infinite factorization of multiple non-parametric views. Machine Learning 79(1-2): 201-226 (2010) - Roger Luis, Luis Enrique Sucar, Eduardo F. Morales:
Inductive transfer for learning Bayesian networks. Machine Learning 79(1-2): 227-255 (2010) - Dragos D. Margineantu, Weng-Keen Wong, Denver Dash:
Machine learning algorithms for event detection. Machine Learning 79(3): 257-259 (2010) - Daniel B. Neill, Gregory F. Cooper:
A multivariate Bayesian scan statistic for early event detection and characterization. Machine Learning 79(3): 261-282 (2010) - Daniel Nikovski, Ankur Jain:
Fast adaptive algorithms for abrupt change detection. Machine Learning 79(3): 283-306 (2010) - Gaurav Tandon, Philip K. Chan:
Increasing coverage to improve detection of network and host anomalies. Machine Learning 79(3): 307-334 (2010) - Tomás Singliar, Milos Hauskrecht:
Learning to detect incidents from noisily labeled data. Machine Learning 79(3): 335-354 (2010) - Cynthia Rudin, Rebecca J. Passonneau, Axinia Radeva, Haimonti Dutta, Steve Ierome, Delfina Isaac:
A process for predicting manhole events in Manhattan. Machine Learning 80(1): 1-31 (2010) - Peter R. Rijnbeek, Jan A. Kors:
Finding a short and accurate decision rule in disjunctive normal form by exhaustive search. Machine Learning 80(1): 33-62 (2010) - Marco C. Campi:
Classification with guaranteed probability of error. Machine Learning 80(1): 63-84 (2010) - Don R. Hush, Reid B. Porter:
Algorithms for optimal dyadic decision trees. Machine Learning 80(1): 85-107 (2010) - Sham Kakade, Ping Li:
Guest editorial: special issue on learning theory. Machine Learning 80(2-3): 109-110 (2010) - Maria-Florina Balcan, Steve Hanneke, Jennifer Wortman Vaughan:
The true sample complexity of active learning. Machine Learning 80(2-3): 111-139 (2010) - Shai Shalev-Shwartz, Yoram Singer:
On the equivalence of weak learnability and linear separability: new relaxations and efficient boosting algorithms. Machine Learning 80(2-3): 141-163 (2010) - Elad Hazan, Satyen Kale:
Extracting certainty from uncertainty: regret bounded by variation in costs. Machine Learning 80(2-3): 165-188 (2010) - Nir Ailon, Mehryar Mohri:
Preference-based learning to rank. Machine Learning 80(2-3): 189-211 (2010) - Ohad Shamir, Naftali Tishby:
Stability and model selection in k-means clustering. Machine Learning 80(2-3): 213-243 (2010) - Robert Kleinberg, Alexandru Niculescu-Mizil, Yogeshwer Sharma:
Regret bounds for sleeping experts and bandits. Machine Learning 80(2-3): 245-272 (2010) - Eric Blais, Ryan O'Donnell, Karl Wimmer:
Polynomial regression under arbitrary product distributions. Machine Learning 80(2-3): 273-294 (2010) - Shuheng Zhou, John D. Lafferty, Larry A. Wasserman:
Time varying undirected graphs. Machine Learning 80(2-3): 295-319 (2010) - José L. Balcázar, Francesco Bonchi, Aristides Gionis, Michèle Sebag:
Special issue for ECML PKDD 2010: Guest editors' introduction. Machine Learning 81(1): 1-4 (2010) - Lan Du, Wray L. Buntine, Huidong Jin:
A segmented topic model based on the two-parameter Poisson-Dirichlet process. Machine Learning 81(1): 5-19 (2010) - Jason Weston, Samy Bengio, Nicolas Usunier:
Large scale image annotation: learning to rank with joint word-image embeddings. Machine Learning 81(1): 21-35 (2010) - Dijun Luo, Heng Huang, Chris H. Q. Ding, Feiping Nie:
On the eigenvectors of p-Laplacian. Machine Learning 81(1): 37-51 (2010) - Ni Lao, William W. Cohen:
Relational retrieval using a combination of path-constrained random walks. Machine Learning 81(1): 53-67 (2010) - Wei Liu, Sanjay Chawla:
Mining adversarial patterns via regularized loss minimization. Machine Learning 81(1): 69-83 (2010) - Ali Nouri, Michael L. Littman:
Dimension reduction and its application to model-based exploration in continuous spaces. Machine Learning 81(1): 85-98 (2010) - Arvind Agarwal, Hal Daumé III:
A geometric view of conjugate priors. Machine Learning 81(1): 99-113 (2010) - Pavel Laskov, Richard Lippmann:
Machine learning in adversarial environments. Machine Learning 81(2): 115-119 (2010) - Marco Barreno, Blaine Nelson, Anthony D. Joseph, J. D. Tygar:
The security of machine learning. Machine Learning 81(2): 121-148 (2010) - Ofer Dekel, Ohad Shamir, Lin Xiao:
Learning to classify with missing and corrupted features. Machine Learning 81(2): 149-178 (2010) - Yingbo Song, Michael E. Locasto, Angelos Stavrou, Angelos D. Keromytis, Salvatore J. Stolfo:
On the infeasibility of modeling polymorphic shellcode - Re-thinking the role of learning in intrusion detection systems. Machine Learning 81(2): 179-205 (2010) - Jacob Abernethy, Olivier Chapelle, Carlos Castillo:
Graph regularization methods for Web spam detection. Machine Learning 81(2): 207-225 (2010) - Peter A. Flach:
The Machine Learning journal: 250 issues and counting. Machine Learning 81(3): 227-228 (2010) - Sylvain Ferrandiz, Marc Boullé:
Bayesian instance selection for the nearest neighbor rule. Machine Learning 81(3): 229-256 (2010) - Ioannis Partalas, Grigorios Tsoumakas, Ioannis P. Vlahavas:
An ensemble uncertainty aware measure for directed hill climbing ensemble pruning. Machine Learning 81(3): 257-282 (2010) - Sertan Girgin, Faruk Polat, Reda Alhajj:
Improving reinforcement learning by using sequence trees. Machine Learning 81(3): 283-331 (2010) - Andrey Bernstein, Nahum Shimkin:
Adaptive-resolution reinforcement learning with polynomial exploration in deterministic domains. Machine Learning 81(3): 359-397 (2010) - Xi-Zhao Wang:
International journal of machine learning and cybernetics. Int. J. Machine Learning & Cybernetics 1(1-4): 1-2 (2010) - Kevin Small, Dan Roth:
Margin-based active learning for structured predictions. Int. J. Machine Learning & Cybernetics 1(1-4): 3-25 (2010) - Battista Biggio, Giorgio Fumera, Fabio Roli:
Multiple classifier systems for robust classifier design in adversarial environments. Int. J. Machine Learning & Cybernetics 1(1-4): 27-41 (2010) - Yin Zhang, Rong Jin, Zhi-Hua Zhou:
Understanding bag-of-words model: a statistical framework. Int. J. Machine Learning & Cybernetics 1(1-4): 43-52 (2010) - Ludmila I. Kuncheva:
Full-class set classification using the Hungarian algorithm. Int. J. Machine Learning & Cybernetics 1(1-4): 53-61 (2010) - Qinghua Hu, Wei Pan, Shuang An, Peijun Ma, Jin-Mao Wei:
An efficient gene selection technique for cancer recognition based on neighborhood mutual information. Int. J. Machine Learning & Cybernetics 1(1-4): 63-74 (2010) - Dong-Ling Tong, Robert Mintram:
Genetic Algorithm-Neural Network (GANN): a study of neural network activation functions and depth of genetic algorithm search applied to feature selection. Int. J. Machine Learning & Cybernetics 1(1-4): 75-87 (2010) - Nita H. Shah, Kunal T. Shukla:
Optimal production schedule in declining market for an imperfect production system. Int. J. Machine Learning & Cybernetics 1(1-4): 89-99 (2010) - Yizhao Ni, Craig Saunders, Sándor Szedmák, Mahesan Niranjan:
The application of structured learning in natural language processing. Machine Translation 24(2): 71-85 (2010) - Walter Daelemans:
Colin de la Higuera: Grammatical inference: learning automata and grammars - Cambridge University Press, 2010, iv + 417 pages. Machine Translation 24(3-4): 291-293 (2010) - Loris Nanni, Alessandra Lumini, Sheryl Brahnam:
Advanced machine learning techniques for microarray spot quality classification. Neural Computing and Applications 19(3): 471-475 (2010) - Roland Memisevic, Geoffrey E. Hinton:
Learning to Represent Spatial Transformations with Factored Higher-Order Boltzmann Machines. Neural Computation 22(6): 1473-1492 (2010) - Emma C. Robinson, Alexander Hammers, Anders Ericsson, A. David Edwards, Daniel Rueckert:
Identifying population differences in whole-brain structural networks: A machine learning approach. NeuroImage 50(3): 910-919 (2010) - Ying Wang, Yong Fan, Priyanka Bhatt, Christos Davatzikos:
High-dimensional pattern regression using machine learning: From medical images to continuous clinical variables. NeuroImage 50(4): 1519-1535 (2010) - Rong Chen, Edward Herskovits:
Machine-learning techniques for building a diagnostic model for very mild dementia. NeuroImage 52(1): 234-244 (2010) - Miles Osborne:
Learning Machine Translation, edited by Cyril Goutte, Nicola Cancedda, Marc Dymetman and George Foster. MIT Press, 2009. Natural Language Engineering 16(1): 99-100 (2010) - Daniel M. Messinger, Paul Ruvolo, Naomi V. Ekas, Alan Fogel:
Applying machine learning to infant interaction: The development is in the details. Neural Networks 23(8-9): 1004-1016 (2010) - Edward Rosten, Reid Porter, Tom Drummond:
Faster and Better: A Machine Learning Approach to Corner Detection. IEEE Trans. Pattern Anal. Mach. Intell. 32(1): 105-119 (2010) - Tal Kenig, Zvi Kam, Arie Feuer:
Blind Image Deconvolution Using Machine Learning for Three-Dimensional Microscopy. IEEE Trans. Pattern Anal. Mach. Intell. 32(12): 2191-2204 (2010) - Luz Rello, Pablo Suárez, Ruslan Mitkov:
A machine learning method for identifying impersonal constructions and zero pronouns in Spanish. Procesamiento del Lenguaje Natural 45: 281-285 (2010) - Olatz Arregi, Klara Ceberio, Arantza Díaz de Ilarraza, Iakes Goenaga, Basilio Sierra, Ana Zelaia:
Determination of Features for a Machine Learning Approach to Pronominal Anaphora Resolution in Basque. Procesamiento del Lenguaje Natural 45: 291-294 (2010) - Murat Soysal, Ece Guran Schmidt:
Machine learning algorithms for accurate flow-based network traffic classification: Evaluation and comparison. Perform. Eval. 67(6): 451-467 (2010) - Christelle Reynès, Hélène Host, Anne-Claude Camproux, Guillaume Laconde, Florence Leroux, Anne Mazars, Benoit Deprez, Robin Fahraeus, Bruno O. Villoutreix, Olivier Sperandio:
Designing Focused Chemical Libraries Enriched in Protein-Protein Interaction Inhibitors using Machine-Learning Methods. PLoS Computational Biology 6(3) (2010) - Aurélien Bellet, Marc Bernard, Thierry Murgue, Marc Sebban:
Learning state machine-based string edit kernels. Pattern Recognition 43(6): 2330-2339 (2010) - Sang-Hak Lee, Hyung Il Koo, Nam Ik Cho:
Image segmentation algorithms based on the machine learning of features. Pattern Recognition Letters 31(14): 2325-2336 (2010) - Ferit Akova, Murat Dundar, V. Jo Davisson, E. Daniel Hirleman, Arun K. Bhunia, J. Paul Robinson, Bartek Rajwa:
A machine-learning approach to detecting unknown bacterial serovars. Statistical Analysis and Data Mining 3(5): 289-301 (2010) - Scott D. Bass, Lukasz A. Kurgan:
Discovery of factors influencing patent value based on machine learning in patents in the field of nanotechnology. Scientometrics 82(2): 217-241 (2010) - Lawrence D. Fu, Constantin F. Aliferis:
Using content-based and bibliometric features for machine learning models to predict citation counts in the biomedical literature. Scientometrics 85(1): 257-270 (2010) - Tingting Sun, Wade Trappe, Yanyong Zhang:
Improved AP association management using machine learning. Mobile Computing and Communications Review 14(4): 4-6 (2010) - Ruchika Malhotra, Arvinder Kaur, Guru Gobind Singh:
Application of machine learning methods for software effort prediction. ACM SIGSOFT Software Engineering Notes 35(3): 1-6 (2010) - Nan Liu, Han Wang:
Ensemble Based Extreme Learning Machine. IEEE Signal Process. Lett. 17(8): 754-757 (2010) - Behnood Gholami, Wassim M. Haddad, Allen Tannenbaum:
Relevance Vector Machine Learning for Neonate Pain Intensity Assessment Using Digital Imaging. IEEE Trans. Biomed. Engineering 57(6): 1457-1466 (2010) - Shadab Khan, João Sanches, Rodrigo Ventura:
Robust Band Profile Extraction Using Constrained Nonparametric Machine-Learning Technique. IEEE Trans. Biomed. Engineering 57(10): 2587-2591 (2010) - Yonggang Cao, Zuofeng Li, Feifan Liu, Shashank Agarwal, Qing Zhang, Hong Yu:
An IR-Aided Machine Learning Framework for the BioCreative II.5 Challenge. IEEE/ACM Trans. Comput. Biology Bioinform. 7(3): 454-461 (2010) - Qiang Cheng:
A Sparse Learning Machine for High-Dimensional Data with Application to Microarray Gene Analysis. IEEE/ACM Trans. Comput. Biology Bioinform. 7(4): 636-646 (2010) - Niklas Lavesson:
Learning Machine Learning: A Case Study. IEEE Trans. Education 53(4): 672-676 (2010) - Alberto Fernández, Salvador García, Julián Luengo, Ester Bernadó-Mansilla, Francisco Herrera:
Genetics-Based Machine Learning for Rule Induction: State of the Art, Taxonomy, and Comparative Study. IEEE Trans. Evolutionary Computation 14(6): 913-941 (2010) - Rukshan Batuwita, Vasile Palade:
FSVM-CIL: Fuzzy Support Vector Machines for Class Imbalance Learning. IEEE T. Fuzzy Systems 18(3): 558-571 (2010) - Bo-Chao Cheng, Yi-An Tsai, Guo-Tan Liao, Eui-Seok Byeon:
HMM machine learning and inference for Activities of Daily Living recognition. The Journal of Supercomputing 54(1): 29-42 (2010) - Suleyman Cetintas, Luo Si, Yan Ping Xin, Casey Hord:
Automatic Detection of Off-Task Behaviors in Intelligent Tutoring Systems with Machine Learning Techniques. TLT 3(3): 228-236 (2010) - Tiansi Hu, Yunsi Fei:
QELAR: A Machine-Learning-Based Adaptive Routing Protocol for Energy-Efficient and Lifetime-Extended Underwater Sensor Networks. IEEE Trans. Mob. Comput. 9(6): 796-809 (2010) - Yoan Miche, Antti Sorjamaa, Patrick Bas, Olli Simula, Christian Jutten, Amaury Lendasse:
OP-ELM: optimally pruned extreme learning machine. IEEE Transactions on Neural Networks 21(1): 158-162 (2010) - Ping Sun, Xin Yao:
Sparse approximation through boosting for learning large scale kernel machines. IEEE Transactions on Neural Networks 21(6): 883-894 (2010) - Masayuki Karasuyama, Ichiro Takeuchi:
Multiple incremental decremental learning of support vector machines. IEEE Transactions on Neural Networks 21(7): 1048-1059 (2010) - D. D. Nguyen, K. Matsumoto, Y. Takishima, Kenji Hashimoto:
Condensed Vector Machines: Learning Fast Machine for Large Data. IEEE Transactions on Neural Networks 21(12): 1903-1914 (2010) - Jérôme François, Humberto J. Abdelnur, Radu State, Olivier Festor:
Machine Learning Techniques for Passive Network Inventory. IEEE Transactions on Network and Service Management 7(4): 244-257 (2010) - Mariyam Mirza, Joel Sommers, Paul Barford, Xiaojin Zhu:
A Machine Learning Approach to TCP Throughput Prediction. IEEE/ACM Trans. Netw. 18(4): 1026-1039 (2010) - Rodolphe Héliot, Karunesh Ganguly, Jessica Jimenez, Jose M. Carmena:
Learning in Closed-Loop Brain-Machine Interfaces: Modeling and Experimental Validation. IEEE Transactions on Systems, Man, and Cybernetics, Part B 40(5): 1387-1397 (2010) - Haralampos-G. D. Stratigopoulos, Petros Drineas, Mustapha Slamani, Yiorgos Makris:
RF Specification Test Compaction Using Learning Machines. IEEE Trans. VLSI Syst. 18(6): 998-1002 (2010) - Ioannis Pitas, Vince D. Calhoun, Konstantinos I. Diamantaras:
Guest Editorial: Special Issue on Machine Learning for Signal Processing. Signal Processing Systems 61(1): 1-2 (2010) - Beth Jelfs, Soroush Javidi, Phebe Vayanos, Danilo P. Mandic:
Characterisation of Signal Modality: Exploiting Signal Nonlinearity in Machine Learning and Signal Processing. Signal Processing Systems 61(1): 105-115 (2010) - Cristina Tarín, Lara Traver, Jorge Bondia, Josep Vehí:
A Learning System for Error Detection in Subcutaneous Continuous Glucose Measurement using Support Vector Machines. CCA 2010: 1614-1619 - Zheng Wang, Michael F. P. O'Boyle:
Partitioning streaming parallelism for multi-cores: a machine learning based approach. PACT 2010: 307-318 - Luc De Raedt, Tias Guns, Siegfried Nijssen:
Constraint Programming for Data Mining and Machine Learning. AAAI 2010 - Shreya Amin:
A Step Towards Modeling and Destabilizing Human Trafficking Networks Using Machine Learning Methods. AAAI Spring Symposium: Artificial Intelligence for Development 2010 - Sean T. Green, Abraham D. Flaxman:
Machine Learning Methods for Verbal Autopsy in Developing Countries. AAAI Spring Symposium: Artificial Intelligence for Development 2010 - Jennifer Sleeman, Tim Finin:
A Machine Learning Approach to Linking FOAF Instances. AAAI Spring Symposium: Linked Data Meets Artificial Intelligence 2010 - Sandro Rodriguez Garzon, Michael Cebulla:
Model-Based Personalization within an Adaptable Human-Machine Interface Environment that is Capable of Learning from User Interactions. ACHI 2010: 191-198 - Michael Bloodgood, Chris Callison-Burch:
Bucking the Trend: Large-Scale Cost-Focused Active Learning for Statistical Machine Translation. ACL 2010: 854-864 - Milan Zorman, Sandi Pohorec, Bostjan Brumen:
Opening the Knowledge Tombs - Web Based Text Mining as Approach for Re-evaluation of Machine Learning Rules. ADBIS 2010: 533-542 - Bruno Martins, Ivo Anastácio, Pável Calado:
A Machine Learning Approach for Resolving Place References in Text. AGILE Conf. 2010: 221-236 - Mehdi Yousfi Monod, Atefeh Farzindar, Guy Lapalme:
Supervised Machine Learning for Summarizing Legal Documents. Canadian Conference on AI 2010: 51-62 - Brent Martin, Marina Filipovic, Lara Rennie, David Shaw:
Using Machine Learning to Prescribe Warfarin. AIMSA 2010: 151-160 - Emmanuel Faure, Carla Taramasco, Jacques Demongeot, Louise Duloquin, Benoit Lombardot, Nadine Peyriéras, Paul Bourgine:
Global Strategy of Active Machine Learning for Complex Systems: Embryogenesis Application on Cell Division Detection. AINA Workshops 2010: 802-809 - Md. Saiful Islam, Abdullah Al Mahmud, Md. Rafiqul Islam:
Machine Learning Approaches for Modeling Spammer Behavior. AIRS 2010: 251-260 - Yu-Chieh Wu, Yue-Shi Lee, Jie-Chi Yang, Show-Jane Yen:
A Sparse L2-Regularized Support Vector Machines for Large-Scale Natural Language Learning. AIRS 2010: 340-349 - Ziheng Lin, Yan Gu, Samarjit Chakraborty:
Tuning Machine-Learning Algorithms for Battery-Operated Portable Devices. AIRS 2010: 502-513 - Qinmin Vivian Hu, Zheng Ye, Jimmy Xiangji Huang:
Enhancing Content-Based Image Retrieval Using Machine Learning Techniques. AMT 2010: 383-394 - Abdallah G. Motaal, Neamat El Gayar, Nael F. Osman:
Different Regions Identification in Composite Strain-Encoded (C-SENC) Images Using Machine Learning Techniques. ANNPR 2010: 231-240 - Nesserine Benchettara, Rushed Kanawati, Céline Rouveirol:
Supervised Machine Learning Applied to Link Prediction in Bipartite Social Networks. ASONAM 2010: 326-330 - Michael Brennan, Stacey Wrazien, Rachel Greenstadt:
Using machine learning to augment collaborative filtering of community discussions. AAMAS 2010: 1569-1570 - Qinghua Zheng, Xin Wang, Wanyu Deng, Jun Liu, Xiyuan Wu:
Incremental Projection Vector Machine: A One-Stage Learning Algorithm for High-Dimension Large-Sample Dataset. Australasian Conference on Artificial Intelligence 2010: 132-141 - Wei Zhang, Scott J. Emrich, Erliang Zeng:
A two-stage machine learning approach for pathway analysis. BIBM 2010: 274-279 - Wenan Chen, Charles Cockrell, Kevin Ward, Kayvan Najarian:
Intracranial pressure level prediction in traumatic brain injury by extracting features from multiple sources and using machine learning methods. BIBM 2010: 510-515 - Hesam T. Dashti, Jernej Tonejc, Adel Ardalan, Alireza F. Siahpirani, Sabrina Guettes, Zohreh Sharif, Liya Wang, Amir H. Assadi:
Applications of Machine Learning Methods to Quantifying Phenotypic Traits that Distinguish the Wild Type from the Mutant Arabidopsis Thaliana Seedlings during Root Gravitropism. BIOCOMP 2010: 49-54 - Vasim Mahamuda, Man Chon U, Khaled Rasheed:
Application of Machine Learning Algorithms for Binning Metagenomic Data. BIOCOMP 2010: 68-74 - Yuedong Song, Sarita Azad, Pietro Liò:
A New Approach for Epileptic Seizure Detection using Extreme Learning Machine. BIOSIGNALS 2010: 436-441 - Mircea Namolaru, Albert Cohen, Grigori Fursin, Ayal Zaks, Ari Freund:
Practical aggregation of semantical program properties for machine learning based optimization. CASES 2010: 197-206 - Andréa M. Matsunaga, José A. B. Fortes:
On the Use of Machine Learning to Predict the Time and Resources Consumed by Applications. CCGRID 2010: 495-504 - Isidoro J. Casanova:
Tradinnova-LCS: Dynamic stock portfolio decision-making assistance model with genetic based machine learning. IEEE Congress on Evolutionary Computation 2010: 1-8 - Simone Pellegrini, Thomas Fahringer, Herbert Jordan, Hans Moritsch:
Automatic tuning of MPI runtime parameter settings by using machine learning. Conf. Computing Frontiers 2010: 115-116 - Michael Moeng, Rami G. Melhem:
Applying statistical machine learning to multicore voltage & frequency scaling. Conf. Computing Frontiers 2010: 277-286 - Kayur Patel:
Lowering the barrier to applying machine learning. CHI Extended Abstracts 2010: 2907-2910 - Castrense Savojardo, Piero Fariselli, Pier Luigi Martelli, Priyank Shukla, Rita Casadio:
Prediction of the Bonding State of Cysteine Residues in Proteins with Machine-Learning Methods. CIBB 2010: 98-111 - Gary B. Fogel, Jonathan Tran, Stephen Johnson, David Hecht:
Machine learning approaches for customized docking scores: Modeling of inhibition of Mycobacterium tuberculosis enoyl acyl carrier protein reductase. CIBCB 2010: 1-6 - Samuel W. K. Chan, Lawrence Y. L. Cheung, Mickey W. C. Chong:
A Machine Learning Parser Using an Unlexicalized Distituent Model. CICLing 2010: 121-136 - Iustina Ilisei, Diana Inkpen, Gloria Corpas Pastor, Ruslan Mitkov:
Identification of Translationese: A Machine Learning Approach. CICLing 2010: 503-511 - Sunday Olusanya Olatunji, Imran A. Adeleke:
An Intelligent Framework for the Classification of Premium and Regular Gasoline for Arson and Fuel Spill Investigation Based on Extreme Learning Machines. CICSyN 2010: 13-16 - Asaf Shabtai, Yuval Fledel, Yuval Elovici:
Automated Static Code Analysis for Classifying Android Applications Using Machine Learning. CIS 2010: 329-333 - Mete Eminagaoglu, Saban Eren:
Implementation and comparison of machine learning classifiers for information security risk analysis of a human resources department. CISIM 2010: 187-192 - Santiago Moisés Mola-Velasco:
Wikipedia Vandalism Detection Through Machine Learning: Feature Review and New Proposals - Lab Report for PAN at CLEF 2010. CLEF (Notebook Papers/LABs/Workshops) 2010 - Abul Bashar, Gerard Parr, Sally I. McClean, Bryan W. Scotney, Detlef Nauck:
Machine learning based Call Admission Control approaches: A comparative study. CNSM 2010: 431-434 - Dmitriy Genzel:
Automatically Learning Source-side Reordering Rules for Large Scale Machine Translation. COLING 2010: 376-384 - Krishna Prasad Chitrapura:
Performance Based Display Advertising - A Large Scale Machine Learning Model in Practice. COMAD 2010: 210 - Sankaranarayanan Ananthakrishnan, Rohit Prasad, David Stallard, Prem Natarajan:
A Semi-Supervised Batch-Mode Active Learning Strategy for Improved Statistical Machine Translation. CoNLL 2010: 126-134 - Shane Bergsma, Dekang Lin, Dale Schuurmans:
Improved Natural Language Learning via Variance-Regularization Support Vector Machines. CoNLL 2010: 172-181 - Jun Fujima, Anja Hawlitschek, Imke Hoppe:
Living Machinery - Advantages of Webble Technologies for Teaching and Learning. CSEDU (1) 2010: 215-220 - Ondrej Kreibich, Radislav Smid:
E-Learning Tools for Education and Training in Diagnostics and Machine Condition Monitoring. CSEDU (2) 2010: 357-361 - Ruben-Dario Pinzon-Morales, Álvaro Orozco-Gutiérrez, César Germán Castellanos-Domínguez:
Feature selection using an ensemble of optimal wavelet packet and learning machine: Application to MER signals. CSNDSP 2010: 25-30 - Ke Huang, Haralampos-G. D. Stratigopoulos, Salvador Mir:
Fault diagnosis of analog circuits based on machine learning. DATE 2010: 1761-1766 - Alex Hai Wang:
Detecting Spam Bots in Online Social Networking Sites: A Machine Learning Approach. DBSec 2010: 335-342 - Pedro Henriques dos Santos Teixeira, Ricardo Gomes Clemente, Ronald Andreu Kaiser, Denis Almeida Vieira Jr.:
HOLMES: an event-driven solution to monitor data centers through continuous queries and machine learning. DEBS 2010: 216-221 - Alexander Artikis, Georgios Paliouras, François Portet, Anastasios Skarlatidis:
Logic-based representation, reasoning and machine learning for event recognition. DEBS 2010: 282-293 - Boris Schauerte, Gernot A. Fink:
Web-Based Learning of Naturalized Color Models for Human-Machine Interaction. DICTA 2010: 498-503 - Chérif Mballo, Vladimir Makarenkov:
Using Unsupervised Machine Learning Methods in High-Throughput Screening. DMIN 2010: 392-395 - Anupam Guha, Hyungsin Kim, Ellen Yi-Luen Do:
Automated Clock Drawing Test through Machine Learning and Geometric Analysis. DMS 2010: 311-314 - Javier Alonso, Jordi Torres, Josep Lluis Berral, Ricard Gavaldà:
Adaptive on-line software aging prediction based on machine learning. DSN 2010: 507-516 - Fabio Tango, Marco Botta, Luca Minin, Roberto Montanari:
Non-intrusive Detection of Driver Distraction using Machine Learning Algorithms. ECAI 2010: 157-162 - Stan Matwin, Joseph De Koninck, Amir Hossein Razavi, Ray Reza Amini:
Classification of Dreams Using Machine Learning. ECAI 2010: 169-174 - Orlando Montalvo, Ryan Shaun Joazeiro de Baker, Michael A. Sao Pedro, Adam Nakama, Janice D. Gobert:
Identifying Students' Inquiry Planning Using Machine Learning. EDM 2010: 141-150 - Josep Lluis Berral, Iñigo Goiri, Ramon Nou, Ferran Julià, Jordi Guitart, Ricard Gavaldà, Jordi Torres:
Towards energy-aware scheduling in data centers using machine learning. e-Energy 2010: 215-224 - Maryam Ramezani, Hans Friedrich Witschel, Simone Braun, Valentin Zacharias:
Using Machine Learning to Support Continuous Ontology Development. EKAW 2010: 381-390 - Mikhail F. Kanevski, Vadim Timonin:
Machine learning analysis and modeling of interest rate curves. ESANN 2010 - Bjoern Krollner, Bruce J. Vanstone, Gavin R. Finnie:
Financial time series forecasting with machine learning techniques: a survey. ESANN 2010 - Yuan Lan, Yeng Chai Soh, Guang-Bin Huang:
Random search enhancement of error minimized extreme learning machine. ESANN 2010 - Yoan Miche, Benjamin Schrauwen, Amaury Lendasse:
Machine Learning Techniques based on Random Projections. ESANN 2010 - Syed Nadeem Ahsan, Franz Wotawa:
Impact analysis of SCRs using single and multi-label machine learning classification. ESEM 2010 - Alessandro Murgia, Giulio Concas, Michele Marchesi, Roberto Tonelli:
A machine learning approach for text categorization of fixing-issue commits on CVS. ESEM 2010 - Leonardo Vanneschi, Antonella Farinaccio, Mario Giacobini, Giancarlo Mauri, Marco Antoniotti, Paolo Provero:
Identification of Individualized Feature Combinations for Survival Prediction in Breast Cancer: A Comparison of Machine Learning Techniques. EvoBIO 2010: 110-121 - Niki Shakeri, Nastaran Nemati, Majid Nili Ahmadabadi, Zainalabedin Navabi:
Near optimal machine learning based random test generation. EWDTS 2010: 420-424 - Cassondra Puklavage, Alexander R. Pirela, Avelino J. Gonzalez, Michael Georgiopoulos:
Imitating Personalized Expressions in an Avatar through Machine Learning. FLAIRS Conference 2010 - Ellen Lowenfeld Walker:
Recognizing American Sign Language Letters: A Machine Learning Experience in an Introductory AI Course. FLAIRS Conference 2010 - Kenneth L. Clarkson, Elad Hazan, David P. Woodruff:
Sublinear Optimization for Machine Learning. FOCS 2010: 449-457 - Yang Li, Fusheng Yu:
Optimized fuzzy information granulation based machine learning classification. FSKD 2010: 259-263 - Krisztián Balázs, János Botzheim, László T. Kóczy:
Comparative analysis of interpolative and non-interpolative fuzzy rule based machine learning systems applying various numerical optimization methods. FUZZ-IEEE 2010: 1-8 - Federico Montesino-Pouzols, Amaury Lendasse:
Evolving fuzzy Optimally Pruned Extreme Learning Machine: A comparative analysis. FUZZ-IEEE 2010: 1-8 - Tomasz Oliwa, Khaled Rasheed:
A Machine Learning Approach for Sensitivity Inference in Genetic Algorithms. GEM 2010: 36-41 - Alberto Tellaeche, Ramón Arana, Aitor Ibarguren, José María Martínez-Otzeta:
Automatic Quality Inspection of Percussion Cap Mass Production by Means of 3D Machine Vision and Machine Learning Techniques. HAIS (1) 2010: 270-277 - Carmen Vidaurre, Claudia Sannelli, Klaus-Robert Müller, Benjamin Blankertz:
Machine-Learning Based Co-adaptive Calibration: A Perspective to Fight BCI Illiteracy. HAIS (1) 2010: 413-420 - Noel Lopes, Bernardete Ribeiro, Ricardo Quintas:
GPUMLib: A new Library to combine Machine Learning algorithms with Graphics Processing Units. HIS 2010: 229-232 - Janne Laaksonen, Ville Kyrki, Danica Kragic:
Evaluation of feature representation and machine learning methods in grasp stability learning. Humanoids 2010: 112-117 - Roy S. Freedman, Isidore Sobkowski:
Surveillance of Parimutuel Wagering Integrity Using Expert Systems and Machine Learning. IAAI 2010 - Shivaram Kalyanakrishnan, Ambarish Goswami:
Predicting Falls of a Humanoid Robot through Machine Learning. IAAI 2010 - Junaith Shahabdeen, Amit Baxi, Lama Nachman:
Ambulatory Energy Expenditure Estimation: A Machine Learning Approach. IAAI 2010 - Philip A. Warrick, Emily F. Hamilton, Robert E. Kearney, Doina Precup:
A Machine Learning Approach to the Detection of Fetal Hypoxia during Labor and Delivery. IAAI 2010 - Olatz Arregi, Klara Ceberio, Arantza Díaz de Ilarraza Sánchez, Iakes Goenaga, Basilio Sierra, Ana Zelaia:
A First Machine Learning Approach to Pronominal Anaphora Resolution in Basque. IBERAMIA 2010: 234-243 - Elisabetta Fersini, Enza Messina, Daniele Toscani, Francesco Archetti, Mauro Cislaghi:
Semantics and Machine Learning for Building the Next Generation of Judicial Court Management Systems. KMIS 2010: 51-60 - Elina Parviainen, Jaakko Riihimäki, Yoan Miche, Amaury Lendasse:
Interpreting Extreme Learning Machine as an Approximation to an Infinite Neural Network. KDIR 2010: 65-73 - Moreno Carullo, Elisabetta Binaghi:
Machine Learning and Link Analysis for Web Content Mining. KDIR 2010: 156-161 - Mikalai Krapivin, Aliaksandr Autayeu, Maurizio Marchese, Enrico Blanzieri, Nicola Segata:
Keyphrases Extraction from Scientific Documents: Improving Machine Learning Approaches with Natural Language Processing. ICADL 2010: 102-111 - Hesam T. Dashti, Adel Ardalan, Alireza F. Siahpirani, Jernej Tonejc, Ioan Vlad Uilecan, Tiago Simas, Bruno Miranda, Rita Almeida Ribeiro, Liya Wang, Amir H. Assadi:
Pattern Recognition in Collective Cognitive Systems: Hybrid Human-Machine Learning (HHML) By Heterogeneous Ensembles. IC-AI 2010: 183-188 - David A. Ostrowski, George Schleis:
Applying Machine Learning Techniques for Knowledge-Based Credit Verification. IC-AI 2010: 249-254 - Amine Trabelsi, Claude Frasson:
The Emotional Machine: A Machine Learning Approach to Online Prediction of User's Emotion and Intensity. ICALT 2010: 613-617 - Jun Zheng, Hui Yu, Furao Shen, Jinxi Zhao:
An Online Incremental Learning Support Vector Machine for Large-scale Data. ICANN (2) 2010: 76-81 - Asja Fischer, Christian Igel:
Empirical Analysis of the Divergence of Gibbs Sampling Based Learning Algorithms for Restricted Boltzmann Machines. ICANN (3) 2010: 208-217 - Maurizio Fiasché, Maria Cuzzola, Roberta Fedele, Pasquale Iacopino, Francesco Carlo Morabito:
Machine Learning and Personalized Modeling Based Gene Selection for Acute GvHD Gene Expression Data Analysis. ICANN (1) 2010: 217-223 - Ernesto Iacucci, Yves Moreau:
Towards Better Receptor-Ligand Prioritization: How Machine Learning on Protein-Protein Interaction Data Can Provide Insight Into Receptor-Ligand Pairs. ICANN (1) 2010: 267-271 - Shogo Okada, Osamu Hasegawa, Toyoaki Nishida:
Machine Learning Approaches for Time-Series Data Based on Self-Organizing Incremental Neural Network. ICANN (3) 2010: 541-550 - Gopalan Vani, Ramaswamy Savitha, Narasimhan Sundararajan:
Classification of abnormalities in digitized mammograms using Extreme Learning Machine. ICARCV 2010: 2114-2117 - Marcin Michalak, Adam Switonski:
Spectrum Evaluation on Multispectral Images by Machine Learning Techniques. ICCVG (2) 2010: 126-133 - B. Celia, I. Felci Rajam:
An Efficient Content Based Image Retrieval Framework Using Machine Learning Techniques. ICDEM 2010: 162-169 - V. P. Abeera, S. Aparna, R. U. Rekha, M. Anand Kumar, V. Dhanalakshmi, K. P. Soman, S. Rajendran:
Morphological Analyzer for Malayalam Using Machine Learning. ICDEM 2010: 252-254 - T. Subbulakshmi, S. Mercy Shalinie, A. Ramamoorthi:
Masquerader Classification System with Linux Command Sequences Using Machine Learning Algorithms. ICDEM 2010: 296-302 - Dan Zhang, Yan Liu, Richard D. Lawrence, Vijil Chenthamarakshan:
ALPOS: A Machine Learning Approach for Analyzing Microblogging Data. ICDM Workshops 2010: 1265-1272 - Qi Guo, Tianshi Chen, Haihua Shen, Yunji Chen:
Estimating design quality of digital systems via machine learning. ICECS 2010: 623-626 - Abdul Adeel Mohammed, Q. M. Jonathan Wu, Maher A. Sid-Ahmed:
Application of Wave Atoms Decomposition and Extreme Learning Machine for Fingerprint Classification. ICIAR (2) 2010: 246-255 - Yibin Ye, Stefano Squartini, Francesco Piazza:
Incremental-Based Extreme Learning Machine Algorithms for Time-Variant Neural Networks. ICIC (1) 2010: 9-16 - Hui-Ping Cheng, Zheng-Sheng Lin, Hsiao-Fen Hsiao, Ming-Lang Tseng:
Designing an Artificial Immune System-Based Machine Learning Classifier for Medical Diagnosis. ICICA (LNCS) 2010: 333-341 - Hamid Reza Vaezi Joze, Mark S. Drew:
Improved machine learning for image category recognition by local color constancy. ICIP 2010: 3881-3884 - Ali H. Shoeb, John V. Guttag:
Application of Machine Learning To Epileptic Seizure Detection. ICML 2010: 975-982 - Ulrich Weiss, Peter Biber, Stefan Laible, Karsten Bohlmann, Andreas Zell:
Plant Species Classification Using a 3D LIDAR Sensor and Machine Learning. ICMLA 2010: 339-345 - Lana Yeganova, Donald C. Comeau, W. John Wilbur:
Identifying Abbreviation Definitions Machine Learning with Naturally Labeled Data. ICMLA 2010: 499-505 - Halil-Ibrahim Bulbul, Özkan Ünsal:
Determination of Vocational Fields with Machine Learning Algorithm. ICMLA 2010: 710-713 - Thashmee Karunaratne, Henrik Boström, Ulf Norinder:
Pre-Processing Structured Data for Standard Machine Learning Algorithms by Supervised Graph Propositionalization - A Case Study with Medicinal Chemistry Datasets. ICMLA 2010: 828-833 - Jian Zhang:
The Influence Machine: Nonnegative Instance-Space Learning with Differentiated Regularization. ICMLA 2010: 861-866 - Jan Outrata:
Boolean Factor Analysis for Data Preprocessing in Machine Learning. ICMLA 2010: 899-902 - Abid M. Malik:
Spatial Based Feature Generation for Machine Learning Based Optimization Compilation. ICMLA 2010: 925-930 - Yu-Feng Liu, Liwei Zhang, Jian Liang, Sheng Qu, Zhiqiang Ni:
Detecting Trojan horses based on system behavior using machine learning method. ICMLC 2010: 855-860 - Chih-Chung Wang, Chien-Wei Lee, Chen-Sen Ouyang:
A machine-learning-based fault diagnosis approach for intelligent condition monitoring. ICMLC 2010: 2921-2926 - Dong-Liang Lee, Chun-Liang Hsu, Sheng-Yuan Yang, Wei-Ying Chen:
Initiated language learning machine with multi-media and speech-recognition techniques. ICMLC 2010: 2985-2989 - Bin Lu, Benjamin K. Tsou:
Combining a large sentiment lexicon and machine learning for subjectivity classification. ICMLC 2010: 3311-3316