Corrective feedback and persistent learning for information extraction A Culotta, T Kristjansson, A McCallum, P Viola Artificial Intelligence 170 (14), 1101-1122, 2006 | 61 | 2006 |
Semi-supervised sequence modeling with syntactic topic models W Li, A McCallum Proceedings of the National Conference on Artificial Intelligence 20 (2), 813, 2005 | 61 | 2005 |
Group and topic discovery from relations and their attributes X Wang, N Mohanty, A McCallum MASSACHUSETTS UNIV AMHERST DEPT OF COMPUTER SCIENCE, 2006 | 60 | 2006 |
Sparse forward-backward using minimum divergence beams for fast training of conditional random fields C Pal, C Sutton, A McCallum Acoustics, Speech and Signal Processing, 2006. ICASSP 2006 Proceedings. 2006 ..., 2006 | 57 | 2006 |
Alternating projections for learning with expectation constraints K Bellare, G Druck, A McCallum Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial ..., 2009 | 55 | 2009 |
Implicit surface modelling with a globally regularised basis of compact support C Walder, B Schölkopf, O Chapelle Computer Graphics Forum 25 (3), 635-644, 2006 | 53 | 2006 |
Fast and robust joint models for biomedical event extraction S Riedel, A McCallum Proceedings of the Conference on Empirical Methods in Natural Language ..., 2011 | 52 | 2011 |
Scalable probabilistic databases with factor graphs and MCMC M Wick, A McCallum, G Miklau Proceedings of the VLDB Endowment 3 (1-2), 794-804, 2010 | 52 | 2010 |
Gene prediction with conditional random fields A Culotta, D Kulp, A McCallum | 51 | 2005 |
Sign detection in natural images with conditional random fields J Weinman, A Hanson, A McCallum Machine Learning for Signal Processing, 2004. Proceedings of the 2004 14th ..., 2004 | 49 | 2004 |
Model combination for event extraction in BioNLP 2011 S Riedel, D McClosky, M Surdeanu, A McCallum, CD Manning Proceedings of the BioNLP Shared Task 2011 Workshop, 51-55, 2011 | 48 | 2011 |
Composition of conditional random fields for transfer learning C Sutton, A McCallum Proceedings of the conference on Human Language Technology and Empirical ..., 2005 | 47 | 2005 |
Method for learning and combining global and local regularities for information extraction and classification DW Quass, TM Mitchell, AK McCallum, W Cohen US Patent 6,892,189, 2005 | 47* | 2005 |
Dynamic conditional random fields for jointly labeling multiple sequences A McCallum, K Rohanimanesh, C Sutton NIPS-2003 Workshop on Syntax, Semantics and Statistics, 2003 | 47 | 2003 |
An exploration of entity models, collective classification and relation description H Raghavan, J Allan, A McCallum | 46 | 2004 |
Piecewise training for structured prediction C Sutton, A McCallum Machine learning 77 (2-3), 165-194, 2009 | 43 | 2009 |
Improved dynamic schedules for belief propagation C Sutton, A McCallum arXiv preprint arXiv:1206.5291, 2012 | 42 | 2012 |
Robust biomedical event extraction with dual decomposition and minimal domain adaptation S Riedel, A McCallum Proceedings of the BioNLP Shared Task 2011 Workshop, 46-50, 2011 | 42 | 2011 |
An Entity Based Model for Coreference Resolution. ML Wick, A Culotta, K Rohanimanesh, A McCallum SDM 9, 365-376, 2009 | 42 | 2009 |
Learning extractors from unlabeled text using relevant databases K Bellare, A McCallum Sixth international workshop on information integration on the web, 2007 | 41 | 2007 |
Samplerank: Training factor graphs with atomic gradients K Rohanimanesh, K Bellare, A Culotta, A McCallum, ML Wick Proceedings of the 28th International Conference on Machine Learning (ICML ..., 2011 | 40 | 2011 |
A unified approach for schema matching, coreference and canonicalization ML Wick, K Rohanimanesh, K Schultz, A McCallum Proceedings of the 14th ACM SIGKDD international conference on Knowledge ..., 2008 | 40 | 2008 |
Joint parsing and semantic role labeling C Sutton, A McCallum Proceedings of the Ninth Conference on Computational Natural Language ..., 2005 | 40 | 2005 |
Lightly-supervised attribute extraction K Bellare, PP Talukdar, G Kumaran, F Pereira, M Liberman, A McCallum, ... | 39 | 2007 |
Semi-supervised learning of dependency parsers using generalized expectation criteria G Druck, G Mann, A McCallum Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL ..., 2009 | 38 | 2009 |
Bi-directional joint inference for entity resolution and segmentation using imperatively-defined factor graphs S Singh, K Schultz, A McCallum Machine Learning and Knowledge Discovery in Databases, 414-429, 2009 | 37 | 2009 |
Generalized expectation criteria A McCallum, G Mann, G Druck Computer science technical note, University of Massachusetts, Amherst, MA, 2007 | 37 | 2007 |
A hierarchical probabilistic model for novelty detection in text LD Baker, T Hofmann, A McCallum, Y Yang Proceedings of International Conference on Machine Learning, 1999 | 37 | 1999 |
Efficient computation of entropy gradient for semi-supervised conditional random fields GS Mann, A McCallum Human Language Technologies 2007: The Conference of the North American ..., 2007 | 36 | 2007 |
A note on topical n-grams X Wang, A McCallum MASSACHUSETTS UNIV AMHERST DEPT OF COMPUTER SCIENCE, 2005 | 36 | 2005 |
Learning with scope, with application to information extraction and classification DM Blei, JA Bagnell, AK McCallum Proceedings of the Eighteenth conference on Uncertainty in artificial ..., 2002 | 35 | 2002 |
Exploring the use of conditional random field models and HMMs for historical handwritten document recognition S Feng, R Manmatha, A McCallum Document Image Analysis for Libraries, 2006. DIAL'06. Second International ..., 2006 | 34 | 2006 |
Reducing weight undertraining in structured discriminative learning C Sutton, M Sindelar, A McCallum Proceedings of the main conference on Human Language Technology Conference ..., 2006 | 33 | 2006 |
Direct maximization of rank-based metrics for information retrieval DA Metzler, WB Croft, A McCallum | 33 | 2005 |
Learning to predict the quality of contributions to wikipedia G Druck, G Miklau, A McCallum WikiAI 8, 7-12, 2008 | 31 | 2008 |
Learning to understand the Web WW Cohen, A McCallum, D Quass IEEE Data Eng. Bull. 23 (3), 17-24, 2000 | 31 | 2000 |
Gibbs sampling for logistic normal topic models with graph-based priors D Mimno, HM Wallach, A McCallum | 30 | 2008 |
A demographic analysis of online sentiment during hurricane irene B Mandel, A Culotta, J Boulahanis, D Stark, B Lewis, J Rodrigue Proceedings of the Second Workshop on Language in Social Media, 27-36, 2012 | 29 | 2012 |
Samplerank: Learning preferences from atomic gradients M Wick, K Rohanimanesh, A Culotta, A McCallum NIPS Workshop on Advances in Ranking, 69-73, 2009 | 29 | 2009 |
The author-recipient-topic model for topic and role discovery in social networks, with application to Enron and academic email A McCallum, A Corrada-Emmanuel, X Wang Workshop on Link Analysis, Counterterrorism and Security, 33-44, 2005 | 29 | 2005 |
Information extraction from the world wide web W Cohen, A McCallum Tutorial Note of The Ninth ACM SIGKDD International Conference on Knowledge ..., 2003 | 29 | 2003 |
Using transitional proximity for faster reinforcement learning RA McCallum Proceedings of the ninth international workshop on Machine learning, 316-321, 2014 | 28 | 2014 |
Transition-based Dependency Parsing with Selectional Branching. JD Choi, A McCallum ACL (1), 1052-1062, 2013 | 28 | 2013 |
High-performance semi-supervised learning using discriminatively constrained generative models G Druck, A McCallum Proceedings of the 27th International Conference on Machine Learning (ICML ..., 2010 | 28 | 2010 |
Joint group and topic discovery from relations and text A McCallum, X Wang, N Mohanty Statistical network analysis: Models, issues, and new directions, 28-44, 2007 | 28 | 2007 |
People-LDA: Anchoring topics to people using face recognition V Jain, E Learned-Miller, A McCallum Computer Vision, 2007. ICCV 2007. IEEE 11th International Conference on, 1-8, 2007 | 27 | 2007 |
Cc prediction with graphical models C Pal, A McCallum | 27 | 2006 |
Efficient non-parametric estimation of multiple embeddings per word in vector space A Neelakantan, J Shankar, A Passos, A McCallum arXiv preprint arXiv:1504.06654, 2015 | 26 | 2015 |
Database of NIH grants using machine-learned categories and graphical clustering EM Talley, D Newman, D Mimno, BW Herr II, HM Wallach, GAPC Burns, ... Nature Methods 8 (6), 443-444, 2011 | 26 | 2011 |
Mining a digital library for influential authors D Mimno, A McCallum Proceedings of the 7th ACM/IEEE-CS joint conference on Digital libraries ..., 2007 | 26 | 2007 |
Learning field compatibilities to extract database records from unstructured text M Wick, A Culotta, A McCallum Proceedings of the 2006 Conference on Empirical Methods in Natural Language ..., 2006 | 26 | 2006 |
First results with utile distinction memory for reinforcement learning RA McCallum University of Rochester, 1992 | 25 | 1992 |
Wikilinks: A large-scale cross-document coreference corpus labeled via links to Wikipedia S Singh, A Subramanya, F Pereira, A McCallum University of Massachusetts, Amherst, Tech. Rep. UM-CS-2012-015, 2012 | 24 | 2012 |
Efficient web spidering with reinforcement learning J Rennie, A McCallum Proceedings of the International Conference on Machine Learning, 1999 | 24 | 1999 |
A discriminative hierarchical model for fast coreference at large scale M Wick, S Singh, A McCallum Proceedings of the 50th Annual Meeting of the Association for Computational ..., 2012 | 22 | 2012 |
Unsupervised deduplication using cross-field dependencies R Hall, C Sutton, A McCallum Proceedings of the 14th ACM SIGKDD international conference on Knowledge ..., 2008 | 22 | 2008 |
Table extraction for answer retrieval X Wei, B Croft, A McCallum Information Retrieval 9 (5), 589-611, 2006 | 21 | 2006 |
Lexicon infused phrase embeddings for named entity resolution A Passos, V Kumar, A McCallum arXiv preprint arXiv:1404.5367, 2014 | 20 | 2014 |
Unsupervised relation discovery with sense disambiguation L Yao, S Riedel, A McCallum Proceedings of the 50th Annual Meeting of the Association for Computational ..., 2012 | 20 | 2012 |
Combining generative and discriminative methods for pixel classification with multi-conditional learning BM Kelm, C Pal, A McCallum Pattern Recognition, 2006. ICPR 2006. 18th International Conference on 2 ..., 2006 | 19 | 2006 |
Feature bagging: Preventing weight undertraining in structured discriminative learning C Sutton, M Sindelar, A McCallum | 19 | 2005 |
Combining joint models for biomedical event extraction D McClosky, S Riedel, M Surdeanu, A McCallum, CD Manning BMC bioinformatics 13 (Suppl 11), S9, 2012 | 18 | 2012 |
Generalized expectation criteria for bootstrapping extractors using record-text alignment K Bellare, A McCallum Proceedings of the 2009 Conference on Empirical Methods in Natural Language ..., 2009 | 17 | 2009 |
Canonicalization of database records using adaptive similarity measures A Culotta, M Wick, R Hall, M Marzilli, A McCallum Proceedings of the 13th ACM SIGKDD international conference on Knowledge ..., 2007 | 17 | 2007 |
Efficient exploration in reinforcement learning with hidden state RA McCallum AAAI Fall Symposium on" Model-directed Autonomous Systems, 1997 | 17 | 1997 |
Efficient strategies for improving partitioning-based author coreference by incorporating Web pages as graph nodes P Kanani, A McCallum Proceedings of AAAI 2007 workshop on information integration on the Web, 38-43, 2007 | 16 | 2007 |
Dynamic sharing and backward compatibility on 64-bit machines WE Garrett, LI Bianchini, LI Kontothanassis, RA McCallum, J Thomas, ... University of Rochester, Department of Computer Science, 1992 | 16 | 1992 |
Joint inference of entities, relations, and coreference S Singh, S Riedel, B Martin, J Zheng, A McCallum Proceedings of the 2013 workshop on Automated knowledge base construction, 1-6, 2013 | 15 | 2013 |
Bayesian modeling of dependency trees using hierarchical Pitman-Yor priors HM Wallach, C Sutton, A McCallum | 15 | 2008 |
Penn/umass/chop biocreative ii systems K Ganchev, K Crammer, F Pereira, G Mann, K Bellare, A McCallum, ... | 15 | 2007 |
Selecting actions for resource-bounded information extraction using reinforcement learning PH Kanani, AK McCallum Proceedings of the fifth ACM international conference on Web search and data ..., 2012 | 14 | 2012 |
Query-aware MCMC ML Wick, A McCallum Advances in Neural Information Processing Systems, 2564-2572, 2011 | 14 | 2011 |
Conditional probabilistic context-free grammars C Sutton, A McCallum Master’s thesis, University of Massachusetts, 2004. http://www. cs. umass ..., 2004 | 14 | 2004 |
Monte Carlo MCMC: efficient inference by approximate sampling S Singh, M Wick, A McCallum Proceedings of the 2012 Joint Conference on Empirical Methods in Natural ..., 2012 | 13 | 2012 |
Distantly labeling data for large scale cross-document coreference S Singh, M Wick, A McCallum arXiv preprint arXiv:1005.4298, 2010 | 13 | 2010 |
Factorie: Efficient probabilistic programming via imperative declarations of structure, inference and learning A McCallum, K Rohanemanesh, M Wick, K Schultz, S Singh In Neural Information Processing Systems (NIPS) Workshop on Probabilistic ..., 2008 | 13 | 2008 |
Tractable learning and inference with high-order representations A Culotta, A McCallum | 13 | 2006 |
A conditional model of deduplication for multi-type relational data A Culotta, A McCallum MASSACHUSETTS UNIV AMHERST DEPT OF COMPUTER SCIENCE, 2005 | 13 | 2005 |
Classification models for new event detection G Kumaran, J Allan, A McCallum | 12 | 2004 |
Learning with incomplete selective perception RA McCallum University of Rochester [Department of] Computer Science, 1993 | 12 | 1993 |
Probabilistic databases of universal schema L Yao, S Riedel, A McCallum Proceedings of the Joint Workshop on Automatic Knowledge Base Construction ..., 2012 | 11 | 2012 |
Joint inference for natural language processing A McCallum Proceedings of the Thirteenth Conference on Computational Natural Language ..., 2009 | 11 | 2009 |
A joint model for discovering and linking entities M Wick, S Singh, H Pandya, A McCallum Proceedings of the 2013 workshop on Automated knowledge base construction, 67-72, 2013 | 10 | 2013 |
Topic models for taxonomies A Bakalov, A McCallum, H Wallach, D Mimno Proceedings of the 12th ACM/IEEE-CS joint conference on Digital Libraries ..., 2012 | 10 | 2012 |
Resource-bounded information gathering for correlation clustering P Kanani, A McCallum Learning Theory, 625-627, 2007 | 10 | 2007 |
Practical Markov logic containing first-order quantifiers with application to identity uncertainty A Culotta, A McCallum Proceedings of the Workshop on Computationally Hard Problems and Joint ..., 2006 | 10 | 2006 |
Universal schema for entity type prediction L Yao, S Riedel, A McCallum Proceedings of the 2013 workshop on Automated knowledge base construction, 79-84, 2013 | 9 | 2013 |
Dynamic knowledge-base alignment for coreference resolution J Zheng, L Vilnis, S Singh, JD Choi, A McCallum | 9 | 2013 |
Piecewise training with parameter independence diagrams: Comparing globally-and locally-trained linear-chain crfs A McCallum, C Sutton | 9 | 2004 |
Parse, price and cut: delayed column and row generation for graph based parsers S Riedel, D Smith, A McCallum Proceedings of the 2012 Joint Conference on Empirical Methods in Natural ..., 2012 | 8 | 2012 |
Distributed map inference for undirected graphical models S Singh, A Subramanya, F Pereira, A McCallum Neural Information Processing Systems (NIPS), Workshop on Learning on Cores ..., 2010 | 8 | 2010 |
Pachinko allocation: Scalable mixture models of topic correlations W Li, A McCallum J. of Machine Learning Research. Submitted, 2008 | 8 | 2008 |
Leveraging existing resources using generalized expectation criteria G Druck, G Mann, A McCallum | 8 | 2007 |
Integrating probabilistic extraction models and relational data mining to discover relations and patterns in text A Culotta, A McCallum, J Betz | 8 | 2006 |
A note on semi-supervised learning using markov random fields W Li, A McCallum | 8 | 2004 |
Learning visual routines with reinforcement learning AK McCallum AAAI Fall Symposium 1996, 82-86, 1996 | 8 | 1996 |
Linking Shared Segments. WE Garrett, ML Scott, R Bianchini, LI Kontothanassis, RA McCallum, ... USENIX Winter, 13-28, 1993 | 8 | 1993 |
Constraint-driven rank-based learning for information extraction S Singh, L Yao, S Riedel, A McCallum Human Language Technologies: The 2010 Annual Conference of the North ..., 2010 | 7 | 2010 |
Resource-bounded information extraction: Acquiring missing feature values on demand P Kanani, A McCallum, S Hu Advances in Knowledge Discovery and Data Mining, 415-427, 2010 | 7 | 2010 |
Interactive learning protocols for natural language applications KM Small | 7 | 2009 |