2008 |
20 | EE | 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 |
19 | EE | 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 |
18 | EE | 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 |
17 | EE | 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) |
2007 |
16 | EE | Murat Dundar,
Balaji Krishnapuram,
Jinbo Bi,
R. Bharat Rao:
Learning Classifiers When the Training Data Is Not IID.
IJCAI 2007: 756-761 |
15 | EE | Shipeng Yu,
Balaji Krishnapuram,
Rómer Rosales,
Harald Steck,
R. Bharat Rao:
Bayesian Co-Training.
NIPS 2007 |
14 | EE | Vikas C. Raykar,
Harald Steck,
Balaji Krishnapuram,
Cary Dehing-Oberije,
Philippe Lambin:
On Ranking in Survival Analysis: Bounds on the Concordance Index.
NIPS 2007 |
13 | EE | 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) |
12 | EE | 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) |
2006 |
11 | EE | 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 |
10 | EE | Volkan Vural,
Glenn Fung,
Balaji Krishnapuram,
Jennifer G. Dy,
R. Bharat Rao:
Batch Classification with Applications in Computer Aided Diagnosis.
ECML 2006: 449-460 |
9 | EE | Glenn Fung,
Murat Dundar,
Balaji Krishnapuram,
R. Bharat Rao:
Multiple Instance Learning for Computer Aided Diagnosis.
NIPS 2006: 425-432 |
8 | EE | 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) |
2005 |
7 | EE | Glenn Fung,
Rómer Rosales,
Balaji Krishnapuram:
Learning Rankings via Convex Hull Separation.
NIPS 2005 |
6 | EE | 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) |
2004 |
5 | EE | Balaji Krishnapuram,
David Williams,
Ya Xue,
Alexander J. Hartemink,
Lawrence Carin,
Mário A. T. Figueiredo:
On Semi-Supervised Classification.
NIPS 2004 |
4 | EE | 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) |
3 | EE | 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) |
2003 |
2 | EE | Balaji Krishnapuram,
Lawrence Carin,
Alexander J. Hartemink:
Joint classifier and feature optimization for cancer diagnosis using gene expression data.
RECOMB 2003: 167-175 |
2002 |
1 | | Balaji Krishnapuram,
Lawrence Carin:
Support Vector Machines for Improved Multiaspect Target Recognition Using the Fisher Scores of Hidden Markov Models.
JCIS 2002: 354-357 |