Keerthi, S. Sathiya

27 publications

AAAI 2022 Efficient Vertex-Oriented Polytopic Projection for Web-Scale Applications Rohan Ramanath, S. Sathiya Keerthi, Yao Pan, Konstantin Salomatin, Kinjal Basu

JMLR 2018 An Efficient Distributed Learning Algorithm Based on Effective Local Functional Approximations Dhruv Mahajan, Nikunj Agrawal, S. Sathiya Keerthi, Sundararajan Sellamanickam, Leon Bottou

AISTATS 2018 Batch-Expansion Training: An Efficient Optimization Framework Michal Derezinski, Dhruv Mahajan, S. Sathiya Keerthi, S. V. N. Vishwanathan, Markus Weimer

JMLR 2017 A Distributed Block Coordinate Descent Method for Training L1 Regularized Linear Classifiers Dhruv Mahajan, S. Sathiya Keerthi, S. Sundararajan

ICML 2017 Gradient Boosted Decision Trees for High Dimensional Sparse Output Si Si, Huan Zhang, S. Sathiya Keerthi, Dhruv Mahajan, Inderjit S. Dhillon, Cho-Jui Hsieh

ECML-PKDD 2013 Tractable Semi-Supervised Learning of Complex Structured Prediction Models Kai-Wei Chang, S. Sundararajan, S. Sathiya Keerthi

ICML 2008 A Dual Coordinate Descent Method for Large-Scale Linear SVM Cho-Jui Hsieh, Kai-Wei Chang, Chih-Jen Lin, S. Sathiya Keerthi, S. Sundararajan

JMLR 2008 Trust Region Newton Method for Logistic Regression Chih-Jen Lin, Ruby C. Weng, S. Sathiya Keerthi

IJCAI 2007 Semi-Supervised Gaussian Process Classifiers Vikas Sindhwani, Wei Chu, S. Sathiya Keerthi

ICML 2007 Trust Region Newton Methods for Large-Scale Logistic Regression Chih-Jen Lin, Ruby C. Weng, S. Sathiya Keerthi

JMLR 2006 Building Support Vector Machines with Reduced Classifier Complexity S. Sathiya Keerthi, Olivier Chapelle, Dennis DeCoste

ICML 2006 Deterministic Annealing for Semi-Supervised Kernel Machines Vikas Sindhwani, S. Sathiya Keerthi, Olivier Chapelle

MLJ 2005 A Fast Dual Algorithm for Kernel Logistic Regression S. Sathiya Keerthi, Kaibo Duan, Shirish K. Shevade, Aun Neow Poo

JMLR 2005 A Modified Finite Newton Method for Fast Solution of Large Scale Linear SVMs S. Sathiya Keerthi, Dennis DeCoste

ICML 2005 Generalized LARS as an Effective Feature Selection Tool for Text Classification with SVMs S. Sathiya Keerthi

ICML 2005 New Approaches to Support Vector Ordinal Regression Wei Chu, S. Sathiya Keerthi

NeCo 2003 Asymptotic Behaviors of Support Vector Machines with Gaussian Kernel S. Sathiya Keerthi, Chih-Jen Lin

NeCo 2003 Bayesian Trigonometric Support Vector Classifier Wei Chu, S. Sathiya Keerthi, Chong Jin Ong

NeCo 2003 SMO Algorithm for Least-Squares SVM Formulation S. Sathiya Keerthi, Shirish K. Shevade

ICML 2002 A Fast Dual Algorithm for Kernel Logistic Regression S. Sathiya Keerthi, Kaibo Duan, Shirish K. Shevade, Aun Neow Poo

MLJ 2002 Convergence of a Generalized SMO Algorithm for SVM Classifier Design S. Sathiya Keerthi, Elmer G. Gilbert

ICML 2001 A Unified Loss Function in Bayesian Framework for Support Vector Regression Wei Chu, S. Sathiya Keerthi, Chong Jin Ong

NeCo 2001 Improvements to Platt's SMO Algorithm for SVM Classifier Design S. Sathiya Keerthi, Shirish K. Shevade, Chiranjib Bhattacharyya, K. R. K. Murthy

JAIR 2001 Mean Field Methods for a Special Class of Belief Networks Chiranjib Bhattacharyya, S. Sathiya Keerthi

NeCo 2001 Predictive Approaches for Choosing Hyperparameters in Gaussian Processes S. Sundararajan, S. Sathiya Keerthi

NeurIPS 2000 A Variational Mean-Field Theory for Sigmoidal Belief Networks Chiranjib Bhattacharyya, S. Sathiya Keerthi

NeurIPS 1999 Predictive App Roaches for Choosing Hyperparameters in Gaussian Processes S. Sundararajan, S. Sathiya Keerthi