Predictive App roaches for Choosing Hyperparameters in Gaussian Processes. - S. Sundararajan; S. Sathiya Keerthi (NIPS, 1999)

Predictive Approaches for Choosing Hyperparameters in Gaussian Processes. - S. Sundararajan; S. Sathiya Keerthi (Neural Comput., 2001)

Predictive Approaches for Sparse Model Learning. - Shirish K. Shevade; S. Sundararajan; S. Sathiya Keerthi (ICONIP, 2004)

Fast Generalized Cross-Validation Algorithm for Sparse Model Learning. - S. Sundararajan; Shirish K. Shevade; S. Sathiya Keerthi (Neural Comput., 2007)

A dual coordinate descent method for large-scale linear SVM. - Cho-Jui Hsieh; Kai-Wei Chang; Chih-Jen Lin; S. Sathiya Keerthi; S. Sundararajan (ICML, 2008)

A sequential dual method for large scale multi-class linear svms. - S. Sathiya Keerthi; S. Sundararajan; Kai-Wei Chang; Cho-Jui Hsieh; Chih-Jen Lin (KDD, 2008)

Active learning in partially supervised classification. - Priyanka Garg; S. Sundararajan (CIKM, 2009)

Semi-Supervised Classification Using Sparse Gaussian Process Regression. - Amrish Patel; S. Sundararajan; Shirish K. Shevade (IJCAI, 2009)

Validation-Based Sparse Gaussian Process Classifier Design. - Shirish K. Shevade; S. Sundararajan (Neural Comput., 2009)

A Sequential Dual Method for Structural SVMs. - Shirish K. Shevade; P. Balamurugan 001; S. Sundararajan; S. Sathiya Keerthi (SDM, 2011)

A Probabilistic Least Squares Approach to Ordinal Regression. - P. K. Srijith; Shirish K. Shevade; S. Sundararajan (Australasian Conference on Artificial Intelligence, 2012)

Validation Based Sparse Gaussian Processes for Ordinal Regression. - P. K. Srijith; Shirish K. Shevade; S. Sundararajan (ICONIP (2), 2012)

Mechanism Design for Cost Optimal PAC Learning in the Presence of Strategic Noisy Annotators. - Dinesh Garg; Sourangshu Bhattacharya; S. Sundararajan; Shirish K. Shevade (UAI, 2012)

Tractable Semi-supervised Learning of Complex Structured Prediction Models. - Kai-Wei Chang; S. Sundararajan; S. Sathiya Keerthi (ECML/PKDD (3), 2013)

Semi-supervised Gaussian Process Ordinal Regression. - P. K. Srijith; Shirish K. Shevade; S. Sundararajan (ECML/PKDD (3), 2013)

A Functional Approximation Based Distributed Learning Algorithm. - Dhruv Mahajan 001; S. Sathiya Keerthi; S. Sundararajan; Léon Bottou (CoRR, 2013)

A Parallel SGD method with Strong Convergence. - Dhruv Mahajan 001; S. Sathiya Keerthi; S. Sundararajan; Léon Bottou (CoRR, 2013)

An Empirical Evaluation of Sequence-Tagging Trainers. - P. Balamurugan 001; Shirish K. Shevade; S. Sundararajan; S. Sathiya Keerthi (CoRR, 2013)

A Distributed Algorithm for Training Nonlinear Kernel Machines. - Dhruv Mahajan 001; S. Sathiya Keerthi; S. Sundararajan (CoRR, 2014)

A distributed block coordinate descent method for training $l_1$ regularized linear classifiers. - Dhruv Mahajan 001; S. Sathiya Keerthi; S. Sundararajan (CoRR, 2014)

Near Real-Time Service Monitoring Using High-Dimensional Time Series. - Shwetabh Khanduja; Vinod Nair; S. Sundararajan; Ameya Raul; Ajesh Babu Shaj; S. Sathiya Keerthi (ICDM Workshops, 2015)

A Simple Label Switching Algorithm for Semisupervised Structural SVMs. - P. Balamurugan 001; Shirish K. Shevade; S. Sundararajan (Neural Comput., 2015)

A Sparse Nonlinear Classifier Design Using AUC Optimization. - Vishal Kakkar; Shirish K. Shevade; S. Sundararajan; Dinesh Garg (SDM, 2017)

A distributed block coordinate descent method for training l1 regularized linear classifiers. - Dhruv Mahajan 001; S. Sathiya Keerthi; S. Sundararajan (J. Mach. Learn. Res., 2017)

VC Dimension Based Fuzzy Sigmoid Neural Network (VC-FSNN). - Linu Pinto; Sasi Gopalan; S. Sundararajan (IEEE Conf. on Intelligent Systems, 2018)

Distributed Newton Methods for Deep Neural Networks. - Chien-Chih Wang; Kent Loong Tan; Chun-Ting Chen; Yu-Hsiang Lin; S. Sathiya Keerthi; Dhruv Mahajan 001; S. Sundararajan; Chih-Jen Lin (Neural Comput., 2018)