Balaji Krishnapuram

Affiliations:
  • IBM


According to our database1, Balaji Krishnapuram authored at least 36 papers between 2002 and 2019.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Online presence:

On csauthors.net:

Bibliography

2019
An Interview with Dr. Balaji Krishnapuram, Winner of SIGKDD Service Award.
SIGKDD Explor., 2019

2015
Predicting readmission risk with institution-specific prediction models.
Artif. Intell. Medicine, 2015

2012
Knowledge discovery system for automated quality abstraction.
SIGHIT Rec., 2012

Building Hospital-Specific Readmission Risk Prediction Models for Heart Failure, Acute Myocardial Infarction and Pneumonia patients.
Proceedings of the AMIA 2012, 2012

2011
Predictive Models in Personalized Medicine: Neural Information Processing Systems (NIPS), 2010 workshop report.
SIGHIT Rec., 2011

Bayesian Co-Training.
J. Mach. Learn. Res., 2011

2010
Designing efficient cascaded classifiers: tradeoff between accuracy and cost.
Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2010

2009
Active Sensing.
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

Using Local Dependencies within Batches to Improve Large Margin Classifiers.
J. Mach. Learn. Res., 2009

2008
Multiple-Instance Learning Algorithms for Computer-Aided Detection.
IEEE Trans. Biomed. Eng., 2008

KDD cup 2008 and the workshop on mining medical data.
SIGKDD Explor., 2008

A Fast Algorithm for Learning a Ranking Function from Large-Scale Data Sets.
IEEE Trans. Pattern Anal. Mach. Intell., 2008

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?.
Proceedings of the Digital Mammography, 2008

Multiple-Instance Learning Improves CAD Detection of Masses in Digital Mammography.
Proceedings of the Digital Mammography, 2008

Bayesian multiple instance learning: automatic feature selection and inductive transfer.
Proceedings of the Machine Learning, 2008

2007
On Classification with Incomplete Data.
IEEE Trans. Pattern Anal. Mach. Intell., 2007

Multi-Task Learning for Classification with Dirichlet Process Priors.
J. Mach. Learn. Res., 2007

A fast algorithm for learning large scale preference relations.
Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics, 2007

Bayesian Co-Training.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

On Ranking in Survival Analysis: Bounds on the Concordance Index.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Training a CAD classifier with correlated data.
Proceedings of the Medical Imaging 2007: Computer-Aided Diagnosis, 2007

Learning Classifiers When the Training Data Is Not IID.
Proceedings of the IJCAI 2007, 2007

2006
Variational Bayes for Continuous Hidden Markov Models and Its Application to Active Learning.
IEEE Trans. Pattern Anal. Mach. Intell., 2006

Multiple Instance Learning for Computer Aided Diagnosis.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

Addressing Image Variability While Learning Classifiers for Detecting Clusters of Micro-calcifications.
Proceedings of the Digital Mammography, 2006

Batch Classification with Applications in Computer Aided Diagnosis.
Proceedings of the Machine Learning: ECML 2006, 2006

2005
Sparse Multinomial Logistic Regression: Fast Algorithms and Generalization Bounds.
IEEE Trans. Pattern Anal. Mach. Intell., 2005

Learning Rankings via Convex Hull Separation.
Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005

2004
A Bayesian Approach to Joint Feature Selection and Classifier Design.
IEEE Trans. Pattern Anal. Mach. Intell., 2004

Joint Classifier and Feature Optimization for Comprehensive Cancer Diagnosis Using Gene Expression Data.
J. Comput. Biol., 2004

On Semi-Supervised Classification.
Proceedings of the Advances in Neural Information Processing Systems 17 [Neural Information Processing Systems, 2004

Generative models and Bayesian model comparison for shape recognition.
Proceedings of the Ninth International Workshop on Frontiers in Handwriting Recognition, 2004

An M-ary KMP classifier for multi-aspect target classification.
Proceedings of the 2004 IEEE International Conference on Acoustics, 2004

2003
Joint classifier and feature optimization for cancer diagnosis using gene expression data.
Proceedings of the Sventh Annual International Conference on Computational Biology, 2003

2002
Support Vector Machines for Improved Multiaspect Target Recognition Using the Fisher Scores of Hidden Markov Models.
Proceedings of the 6th Joint Conference on Information Science, 2002

Support Vector Machines for improved multiaspect target recognition using the fisher kernel scores of Hidden Markov Models.
Proceedings of the IEEE International Conference on Acoustics, 2002


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