Vikas C Raykar  Vikas C Raykar photo       

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India Research Laboratory, Bangalore, India



Data split strategies for evolving predictive models
Vikas C. Raykar and Amrita Saha
ECML PKDD - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2015


AUC dominant unsupervised ensemble of binary classifi ers
P. Agrawal, V. C. Raykar, A. Saha
Proceedings of the 2014 SIAM International Conference on Data Mining

Sequential crowdsourced labeling as an epsilon-greedy exploration in a Markov Decision Process
V. C. Raykar, P. Agrawal
Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, pp. 832--840, 2014


Eliminating Spammers and Ranking Annotators for Crowdsourced Labeling Tasks
V. C. Raykar, S Yu
Journal of Machine Learning Research13, 491-518, 2012


Designing efficient cascaded classifiers: Tradeoff between accuracy and cost
V. C. Raykar, B. Krishnapuram, S. Yu
KDD '10: Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining, pp. 853--860, ACM, 2010

Fast Computation of Kernel Estimators
V. C. Raykar, R. Duraiswami, L. H. Zhao
Journal of Computational and Graphical Statistics 19(1), 205--220, 2010

Learning from crowds
V. C. Raykar, S. Yu, L. H. Zhao, G. H. Valadez, C. Florin, L. Bogoni, L. Moy
Journal of Machine Learning Research11, 1297--1322, 2010


On Ranking in Survival Analysis: Bounds on the Concordance Index
V. C. Raykar, H. Steck, B. Krishnapuram, C. Dehing-Oberije, P. Lambin
Advances in Neural Information Processing Systems 20, 2008

Bayesian Multiple Instance Learning: Automatic Feature Selection and Inductive Transfer
V. C. Raykar, B. Krishnapuram, J. Bi, M. Dundar, R. B. Rao
Proceedings of the 25th International Conference on Machine Learning, pp. 808--815, 2008