62) Shipeng Yu, Glenn Fung, Romer Rosales, Sriram Krishnan, R. Rao Bharat,
Cary Dehing-Oberije, Philippe Lambin, Privacy-Preserving Cox Regression for Survival
Analysis. March 08. Submitted.
61) R Bharat
Rao, Jinbo Bi, Glenn Fung, Marcos Salganicoff, Nancy Obuchowsky and David
Naidich. Improving computer assisted diagnosis for lung cancer detection:
challenges and new algorithms.
Feb 08. In preparation.
60) Phan Giang, Harald Steck and Glenn Fung. A
Statistical Perspective of the Likelihood Gamble Pricing Approach. Feb 08. Submitted.
59) Phan Giang, Harald Steck and Glenn Fung. Likelihood gamble pricing theory and
logistic regression. Feb 08. Submitted.
58) C. Dehing-Oberije, S. Yu, D. De
Ruysscher, S. Meersschout, K. Van Beek,
Y. Lievens, J. Van Meerbeeck, W. De
Neve, G. Fung, B. Rao, S. Krishnan, H. van der Weide, P. Lambin. Development and external validation of a
prognostic model for 2-year survival of non-small cell lung cancer patients
treated with (chemo) radiotherapy Feb. 08. Submitted.
57) Volkan Vural, Glenn Fung, Jennifer Dy and Romer
Rosales. Learning Multi-Class
Classifiers and Their Underlying Shared Class Structure. Submitted Feb 08.
56) P. Bamberger, I. Leichter,
N. Merlet, E. Ratner, G. Fung, A. Lederman. Optimizing
the CAD Process for Detecting Mammographic Lesions by a New Generation
Algorithm Based on Linear Classifiers and a Gradient Based Method. Jan 08.
Submitted.
55) I. Leichter, A. Lederman, E. Ratner,
N. Merlet, G. Fung, B. Krishnapuram, P. Bamberger. Does a mammography CAD algorithm with varying filtering levels of
detection marks, used to reduce the false mark rate, adversely affect the
detection of small masses?. Jan 08. Submitted.
54) Mark Schmidt, Glenn Fung and Romer Rosales. Efficient Optimization Methods for L1
Regularization: Current and New directions. Jan. 08. Submitted.
53) O.L.
Mangasarian, E.W. Wild and Glenn Fung. Privacy-preserving
classification of vertically partitioned data via random kernels. Sept. 07.
Submitted
52) Volkan Vural, Glenn Fung, Balaji Krishnapuram,
Jennifer Dy, Bharat Rao. Using Local Dependencies within Batches to
Improve Large Margin Classifiers. Dec 2007. Submitted.
51) O. L.
Mangasarian, E. W. Wild and Glenn Fung. Proximal
Knowledge-Based Classification. UW-Madison Data Mining Institute Technical
Report 06-05, Nov. 06. Submitted
50) Glenn Fung, Romer Rosales and Bharat Rao. On the Dangers of Cross-Validation. An
Experimental Evaluation.
49) M. Starmans, G. Fung, H. Steck, B. Wouters, P.
Lambin. Validation is the key in microarray signature research. Poster
in the Keystone Symposia on Biomarker Discovery, Validation and Applications. Feb 08.
48) Glenn Fung, Shipeng Yu,
47) Mark Schmidt, Romer Rosales,
Glenn Fung and Kevin Murphy. Structure Learning in Random Fields for Heart
Motion Abnormality Detection. CVPR
2008. Accepted
46) Glenn
Fung, R. Seignauric, S. Krishnan, B. Rao, B. Wouters and P. Lambin. Reducing a biomarkers list via
mathematical programming: Applications to gene signatures to detect
time-dependent hypoxia in Cancer. International conference on machine
learning applications. ICMLA 2007.
45) C.
Dehing, D. De Ruysscher, H. van der Weide, G. Fung, S. Krishnan, R.B. Rao, and
Ph. Lambin. The limitations of dosimetric parameters for the prediction of
radiation-induced lung toxicity: an
approach based on machine learning techniques. Annual meeting of the American
society for therapeutic radiology and oncology (ASTRO) 2007.
44) Glenn
Fung and Hui Chen. Learning sparse
surface similarity functions for automatic heart wall motion abnormality
detection. Innovative Applications of Artificial Intelligence (IAAI) 2008.
Accepted
43) R Bharat
Rao, Jinbo Bi, Glenn Fung, Marcos Salganicoff, Nancy Obuchowsky and David
Naidich. LungCAD: A clinically approved,
machine learning system for lung cancer detection. Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. KDD 2007.
42) Mark
Schmidt, Glenn Fung and Romer Rosales. Fast
Optimization Methods for L1 Regularization: A Comparative Study and Two New
Approaches. Proceedings of the European conference in machine learning. ECML 2007.
41) Glenn
Fung, Romer Rosales. Feature Selection
and Kernel Design via Linear Programming. Proceedings of the International joint Conference in
Artificial intelligence, IJCAI 2007.
40) Volkan Vural, Glenn Fung, Balaji Krishnapuram,
Jennifer Dy, Bharat Rao. Batch-wise
Classification with Applications to Computer Aided Diagnosis. Proceedings
of the European conference in machine learning. ECML 2006.
39) Romer
Rosales, Glenn Fung. Learning Sparse
Metrics via Linear Programming. Proceedings of the ACM SIGKDD
International Conference on Knowledge Discovery and Data Mining, 2006.
38) Maleeha
Qazi, Glenn Fung, Sriram Krishnan, Romer Rosales, Harald Steck, Bharat Rao, Don
Poldermans. Automated Heart Wall Motion
Abnormality Detection from Ultrasound Images Using Segmental Knowledge. Distinguished
Paper Award at the International joint Conference in Artificial intelligence, IJCAI
2007.
37) Jinbo Bi, Senthyl Periaswamy, Kasunori Okada,
Toshiro Kubota, Glenn Fung, Marcos Salganicoff, Bharat Rao. Computer Aided Detection via Asymmetric Cascade of Sparse Hyperplane
Classifiers. Proceedings of the ACM SIGKDD International Conference on
Knowledge Discovery and
Data Mining, 2006.
36) Glenn
Fung, Murat Dundar, Balaji Krishnapuram, Bharat Rao . Multiple Instance Algorithms for Computer Aided Diagnosis . Advances in Neural Information
Processing Systems 15, NIPS 2006.
35) Glenn
Fung, Romer Rosales, Balaji Krishnapuram,
Learning Rankings via Convex
34) A.
Greenberg, W. N. Rom, E. M. Tang, D. Naidich, H. Steck, G. Fung, B. Rao and M.
Salganicoff. Tumor Associated antigens assays (TAA) in
managment of ground glass nodules (GGN) indeterminate in CT. European
Congress of Radiology, ECR 2007, Vienna, Austria, March 9-13, 2007.
33) Glenn
Fung, Balaji Krishnapuram, Sriram Krishnan, and Bharat Rao. Addressing image variability while learning classifiers for detecting
clusters of micro-calcifications, proceedings of the 8th International
Workshop, IWDM 2006,
32) Pascal
Cathier and Glenn Fung. Population
classification using global brain shape features inferred from massive T1-MRI
registration .Poster at the Twelfth Annual Meeting of the Organization for
Human Brain Mapping,
31) J.
Hung, M. Jagen, A. Greenberg, E. Tan, D. Naidich, H. Steck, G. Fung, M.
Salganikoff, R. B. Rao, B Phalan, E. Eylers and W. Rom , Autoantibody Reactivity to Tumor Associated Antigens as a Biomarker for
Early Lung Cancer, poster at the International Conference of the American
Thoracic Society, 2006.
30) A. S.
Katz, S. Krishnan, X. Zhou, B. Georgescu, M. Gera, D. Comaniciu, J. Bi, G.
Fung, J. Liang, B. Rao, R. Grimson, N. Reichek. Clinical Evaluation of a Novel Automatic Real-Time Myocardial Tracking
and Wall Motion Scoring Algorithm for Echocardiography Introduction.
29) Glenn
Fung, Maleeha Qazi, Sriram Krishnan, Jinbo Bi, Bharat Rao, Alan Katz. Sparse classifiers for Automated Heart
Wall Motion Abnormality Detection . Proceedings of the IEEE international
conference on machine learning and its applications. ICMLA 2005.
28) M. Wolf, J.
Stoeckel, M. Salganicoff, G. Fung, M. Dundar, S. Periaswamy, J. Bi and H. Shen.
CAD
Performance Analysis for Pulmonary Nodule Detection on Thin-slice MDCT Scans. CARS 2005 Computer
Assisted Radiology and Surgery, 19th International Congress and Exhibition June
22 - 25, 2005
27) J. Stoeckel and
G. Fung. A Mathematical Programming Approach for Automatic Classification of
SPECT Images of Alzheimer's Disease. Proceedings of the IEEE international conference in data
mining (ICDM) 2005.
26) M. Dundar, G.
Fung, J. Bi, S. Sandilya and B. Rao. Sparse Fisher Discriminant Analysis for
Computer Aided Detection. Proceedings of
the
25) L. Bogoni, A. Jerebko, P. Cathier, S. Periaswamy,
M. Dundar, J. Liang, G. Fung, B. Rao, A. Megibow and M. Macari. Automatic Polyp Detection: CAD System Performance. ESGAR 2004: European Society of
Gastrointestinal and Abdominal Radiology.
24) M. Dundar, G.
Fung, L. Bogoni, M. Macari, A. Megibow, B. Rao. A Methodology for Training and
Validating a CAD System and Potential Pitfalls. CARS 2004 - Computer Assisted Radiology and Surgery, Proceedings of the 18th International
Congress and Exhibition,
23) P. Cathier, S.
Periaswamya, A. Jerebko, M. Dundar, J.Liang, G.Fung, J.Stoeckel, T. Venkat,
R.Amara, A.Krishnan, B.Rao, A.Gupta, E.Vega, S.Laks, A.Megibow, M.Macari and
L.Bogoni. CAD for Polyp Detection: an Invaluable Tool to Meet the Increasing Need
for Colon-Cancer Screening. CARS 2004 - Computer Assisted Radiology and
Surgery.
Proceedings
of the 18th International Congress and Exhibition,
22) G. Fung, S.
Sandilya and B. Rao. Rule Extraction for Hyperplane Classifiers. Proceedings of the
ACM SIGKDD International
Conference on Knowledge Discovery
and Data Mining. KDD 2005.
21) J. Bi , M.
Dundar, G. Fung and B. Rao. Semi-supervised Mixture of Kernels via Generalized LP
Boost.
Proceedings of the IEEE international conference in data mining (ICDM) 2005.
20) G. Fung, M.
Dundar, J. Bi and B. Rao. A Fast Iterative Algorithm For Fisher
Discriminant Using Heterogeneous Kernels. Proceedings of the twenty-first international conference
on machine learning, ICML
2004, 313-320.
19) Glenn Fung. The Disputed
Federalist Papers: SVM and Feature Selection via Concave Minimization. Proceedings of the 2003 Conference of
Diversity in Computing. 2003,
42-46.
18) G. Fung, O. L.
Mangasarian and J. Shavlik. Knowledge-based Nonlinear Kernel Classifiers. Learning Theory and
Kernel Machines. COLT 2003 proceedings, 102-113.
17) G. Fung, O. L.
Mangasarian and J. Shavlik. Knowledge-Based SVM Classifiers. Advances in Neural
Information Processing Systems 15, NIPS 2002, 521-528.
16) G. Fung and O.
L. Mangasarian. Incremental Support Vector Machine Classification. Proceedings of the Second
15) G. Fung and O.
L. Mangasarian. Proximal Support Vector Classifiers. Proceedings of the
Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data
Mining. August 26-29, 2001, 77-86
14) G. Fung and O. L. Mangasarian. Data Selection for SVM Classifiers. Proceedings of the
Sixth ACM SIGKDD International Conference on Knowledge Discovery and Data
Mining. August 20-23, 2000, 64-70.
13) Volkan
Vural, Glenn Fung, Jennifer Dy, Bharat Rao
. Semi-supervised Classifiers using A-priori Metric Information. Jan. 2006,
Optimization Methods and Software Journal, Special Issue in Machine Learning,
to appear.
12) Glenn Fung, Murat Dundar, Balaji Krishnapuram,
Bharat Rao , Multiple Instance Learning algorithms for Computer Aided Detection.
IEEE Transactions in biomedical engineering 2007.
11) Glenn
Fung, Maleeha Qazi, Sriram Krishnan, Jinbo Bi, Bharat Rao, Alan Katz. Automated Heart Wall Motion Abnormality
Detection using Sparse Linear Classifiers. IEEE Engineering on Medicine and
Biology Magazine , special issue in machine learning in life sciences. 2007.
10) G. Fung, S.
Sandilya and B. Rao. Rule Extraction from
Linear Support Vector Machines via Mathematical Programming. Invited chapter in Rule Extraction from Support
Vector Machines, Springer Series:
Studies in Computational Intelligence, Vol. 80. 2008
9) R.
Seigneuric, M. Startmans, G. Fung, B. Krishnapuram, D. Nuyten, A. Van Erk, M.
Magagnin, K. Rouschop, S. Krishnan, B. Rao, C. Evelo, A. Begg, B. Wouters and
P. Lambin. Impact of supervised gene signatures of early
hypoxia on patient survival. Radiotherapy and Oncology journal, 83, (2007)
374-382.
8) Glenn Fung, Jonathan Stoeckel: SVM feature selection for classification of SPECT images of
Alzheimer's disease using spatial information. Knowl. Inf. Syst. 11(2):
243-258 (2007)
7) G. Fung and O. L.
Mangasarian. Breast Tumor Susceptibility to Chemotherapy via Support Vector
Machines. Special Issue on
Support Vector Machines, Journal of Computational Management Science , Vol 3, 2006, 103-112 .
6) G. Fung, O. L.
Mangasarian. A Feature Selection
5) G. Fung, O. L.
Mangasarian. Finite
4) G. Fung, O. L.
Mangasarian. Multicategory Proximal Support Vector Classifiers.
Machine Learning Journal. Volume 59. Numbers 1-2,
pages 77-97. May 2005.
3) G. Fung, O. L.
Mangasarian and A. Smola. Minimal Kernel Classifiers. Journal of Machine
Learning research. Vol 3(Nov): 303-321, 2002.
2) G. Fung and O. L.
Mangasarian. Semi-Supervised Support Vector Machines for Unlabeled Data
Classification. Optimization
Methods and Software 15, 2001, 29-44.
1) D. Cores and G.
Fung. A fast 3D Ray Tracer using Nonlinear Optimization techniques. Journal of Applied Geophysics, Volume
45, Issue 4, 2000, 273-284.