Balaji Krishnapuram

Faisal Farooq, Shipeng Yu, Balaji Krishnapuram, Bharat Rao: Knowledge discovery system for automated quality abstraction. SIGHIT Record 2(1): 17 (2012)

Shipeng Yu, Balaji Krishnapuram, Rómer Rosales, R. Bharat Rao: Bayesian Co-Training. Journal of Machine Learning Research 12: 2649-2680 (2011)

Faisal Farooq, Balaji Krishnapuram, Rómer Rosales, Shipeng Yu, Jude W. Shavlik, Raju Kucherlapati: Predictive Models in Personalized Medicine: Neural Information Processing Systems (NIPS), 2010 workshop report. SIGHIT Record 1(1): 23-25 (2011)

Vikas C. Raykar, Balaji Krishnapuram, Shipeng Yu: Designing efficient cascaded classifiers: tradeoff between accuracy and cost. KDD 2010: 853-860

Bharat Rao, Balaji Krishnapuram, Andrew Tomkins, Qiang Yang (Eds.): Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, July 25-28, 2010. ACM 2010, isbn 978-1-4503-0055-1

Shipeng Yu, Balaji Krishnapuram, Rómer Rosales, R. Bharat Rao: Active Sensing. Journal of Machine Learning Research - Proceedings Track 5: 639-646 (2009)

Volkan Vural, Glenn Fung, Balaji Krishnapuram, Jennifer G. Dy, R. Bharat Rao: Using Local Dependencies within Batches to Improve Large Margin Classifiers. Journal of Machine Learning Research 10: 183-206 (2009)

Vikas C. Raykar, Ramani Duraiswami, Balaji Krishnapuram: A Fast Algorithm for Learning a Ranking Function from Large-Scale Data Sets. IEEE Trans. Pattern Anal. Mach. Intell. 30(7): 1158-1170 (2008)

R. Bharat Rao, Oksana Yakhnenko, Balaji Krishnapuram: KDD cup 2008 and the workshop on mining medical data. SIGKDD Explorations 10(2): 34-38 (2008)

Murat Dundar, Glenn Fung, Balaji Krishnapuram, R. Bharat Rao: Multiple-Instance Learning Algorithms for Computer-Aided Detection. IEEE Trans. Biomed. Engineering 55(3): 1015-1021 (2008)

Vikas C. Raykar, Balaji Krishnapuram, Jinbo Bi, Murat Dundar, R. Bharat Rao: Bayesian multiple instance learning: automatic feature selection and inductive transfer. ICML 2008: 808-815

Balaji Krishnapuram, Jonathan Stoeckel, Vikas C. Raykar, R. Bharat Rao, Philippe Bamberger, Eli Ratner, Nicolas Merlet, Inna Stainvas, Menahem Abramov, Alexandra Manevitch: Multiple-Instance Learning Improves CAD Detection of Masses in Digital Mammography. Digital Mammography / IWDM 2008: 350-357

Isaac Leichter, Richard Lederman, Eli Ratner, Nicolas Merlet, Glenn Fung, Balaji Krishnapuram, Philippe 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?. Digital Mammography / IWDM 2008: 504-509

Vikas C. Raykar, Ramani Duraiswami, Balaji Krishnapuram: A fast algorithm for learning large scale preference relations. Journal of Machine Learning Research - Proceedings Track 2: 388-395 (2007)

Ya Xue, Xuejun Liao, Lawrence Carin, Balaji Krishnapuram: Multi-Task Learning for Classification with Dirichlet Process Priors. Journal of Machine Learning Research 8: 35-63 (2007)

David Williams, Xuejun Liao, Ya Xue, Lawrence Carin, Balaji Krishnapuram: On Classification with Incomplete Data. IEEE Trans. Pattern Anal. Mach. Intell. 29(3): 427-436 (2007)

Murat Dundar, Balaji Krishnapuram, Jinbo Bi, R. Bharat Rao: Learning Classifiers When the Training Data Is Not IID. IJCAI 2007: 756-761

Vikas C. Raykar, Harald Steck, Balaji Krishnapuram, Cary Dehing-Oberije, Philippe Lambin: On Ranking in Survival Analysis: Bounds on the Concordance Index. NIPS 2007

Shipeng Yu, Balaji Krishnapuram, Rómer Rosales, Harald Steck, R. Bharat Rao: Bayesian Co-Training. NIPS 2007

Shihao Ji, Balaji Krishnapuram, Lawrence Carin: Variational Bayes for Continuous Hidden Markov Models and Its Application to Active Learning. IEEE Trans. Pattern Anal. Mach. Intell. 28(4): 522-532 (2006)

Volkan Vural, Glenn Fung, Balaji Krishnapuram, Jennifer G. Dy, R. Bharat Rao: Batch Classification with Applications in Computer Aided Diagnosis. ECML 2006: 449-460

Glenn Fung, Balaji Krishnapuram, Nicolas Merlet, Eli Ratner, Philippe Bamberger, Jonathan Stoeckel, R. Bharat Rao: Addressing Image Variability While Learning Classifiers for Detecting Clusters of Micro-calcifications. Digital Mammography / IWDM 2006: 84-91

Glenn Fung, Murat Dundar, Balaji Krishnapuram, R. Bharat Rao: Multiple Instance Learning for Computer Aided Diagnosis. NIPS 2006: 425-432

Balaji Krishnapuram, Lawrence Carin, Mário A. T. Figueiredo, Alexander J. Hartemink: Sparse Multinomial Logistic Regression: Fast Algorithms and Generalization Bounds. IEEE Trans. Pattern Anal. Mach. Intell. 27(6): 957-968 (2005)

Glenn Fung, Rómer Rosales, Balaji Krishnapuram: Learning Rankings via Convex Hull Separation. NIPS 2005

Balaji Krishnapuram, Lawrence Carin, Alexander J. Hartemink: Joint Classifier and Feature Optimization for Comprehensive Cancer Diagnosis Using Gene Expression Data. Journal of Computational Biology 11(2/3): 227-242 (2004)

Balaji Krishnapuram, Alexander J. Hartemink, Lawrence Carin, Mário A. T. Figueiredo: A Bayesian Approach to Joint Feature Selection and Classifier Design. IEEE Trans. Pattern Anal. Mach. Intell. 26(9): 1105-1111 (2004)

Balaji Krishnapuram, Christopher M. Bishop, Martin Szummer: Generative models and Bayesian model comparison for shape recognition. IWFHR 2004: 20-25

Balaji Krishnapuram, David Williams, Ya Xue, Alexander J. Hartemink, Lawrence Carin, Mário A. T. Figueiredo: On Semi-Supervised Classification. NIPS 2004

Balaji Krishnapuram, Lawrence Carin, Alexander J. Hartemink: Joint classifier and feature optimization for cancer diagnosis using gene expression data. RECOMB 2003: 167-175

Balaji Krishnapuram, Lawrence Carin: Support Vector Machines for improved multiaspect target recognition using the fisher kernel scores of Hidden Markov Models. ICASSP 2002: 2989-2992

Balaji Krishnapuram, Lawrence Carin: Support Vector Machines for Improved Multiaspect Target Recognition Using the Fisher Scores of Hidden Markov Models. JCIS 2002: 354-357