Sathiya Keerthi Selvaraj

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Citations	20122	6308
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Sundararajan SellamanickamSenior Principal Researcher, Microsoft Research, BangaloreVerified email at microsoft.com
Shirish ShevadeIndian Institute of ScienceVerified email at csa.iisc.ernet.in
Chong Jin OngAssociate Professor of Mechanical Engineering, National University of SingaporeVerified email at nus.edu.sg
Elmer GilbertProfessor of EngineeringVerified email at umich.edu
Wei Chu（褚崴）AlibabaVerified email at gatsby.ucl.ac.uk
Chih-Jen LinProfessor of Computer Science, National Taiwan UniversityVerified email at csie.ntu.edu.tw
Chiranjib BhattacharyyaProfessor, Indian Institute of ScienceVerified email at csa.iisc.ernet.in
Olivier ChapelleGoogleVerified email at chapelle.cc
Radha Krishna Murthy KaruturiSenior Director of Computational Sciences, The Jackson LaboratoryVerified email at jax.org
Vikas SindhwaniGoogle BrainVerified email at google.com
Dhruv MahajanResearch Scientist at Computer Vision Group, Facebook AIVerified email at fb.com
Dennis DeCosteAppleVerified email at apple.com
Cho-Jui HsiehUniversity of California, Los AngelesVerified email at cs.ucla.edu
Kai-Wei ChangAssistant Professor, UCLAVerified email at kwchang.net
Zoubin GhahramaniProfessor, University of Cambridge, and Distinguished Researcher, GoogleVerified email at eng.cam.ac.uk
Ruby Chiu-Hsing WengProfessor of Statistics, National Chengchi UniversityVerified email at nccu.edu.tw
Balaraman RavindranProfessor of Computer Science, Indian Institute of Technology MadrasVerified email at cse.iitm.ac.in
Johannes GehrkeMicrosoftVerified email at microsoft.com
Narasimha Murty M/ M. N. Murty/M. N....honorary professor, computer science and automation, indian institute of scienceVerified email at iisc.ac.in
Leon BottouFacebook AI ResearchVerified email at bottou.org

Sathiya Keerthi Selvaraj

Principal Staff Scientist @ LinkedIn, Mountain View

Verified email at linkedin.com - Homepage

Optimization Machine Learning Learning with Structured Outputs Kernel Methods SVMs


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Improvements to Platt's SMO algorithm for SVM classifier design SS Keerthi, SK Shevade, C Bhattacharyya, KRK Murthy Neural computation 13 (3), 637-649, 2001	2105	2001
Asymptotic behaviors of support vector machines with Gaussian kernel SS Keerthi, CJ Lin Neural computation 15 (7), 1667-1689, 2003	2010	2003
A fast procedure for computing the distance between complex objects in three-dimensional space EG Gilbert, DW Johnson, SS Keerthi IEEE Journal on Robotics and Automation 4 (2), 193-203, 1988	1556	1988
Improvements to the SMO algorithm for SVM regression SK Shevade, SS Keerthi, C Bhattacharyya, KRK Murthy IEEE transactions on neural networks 11 (5), 1188-1193, 2000	1027	2000
A dual coordinate descent method for large-scale linear SVM CJ Hsieh, KW Chang, CJ Lin, SS Keerthi, S Sundararajan Proceedings of the 25th international conference on Machine learning, 408-415, 2008	1001	2008
Optimal infinite-horizon feedback laws for a general class of constrained discrete-time systems: Stability and moving-horizon approximations SS Keerthi, EG Gilbert Journal of optimization theory and applications 57 (2), 265-293, 1988	989	1988
Which is the best multiclass SVM method? An empirical study KB Duan, SS Keerthi International workshop on multiple classifier systems, 278-285, 2005	810	2005
Evaluation of simple performance measures for tuning SVM hyperparameters K Duan, SS Keerthi, AN Poo Neurocomputing 51, 41-59, 2003	763	2003
Trust region newton method for logistic regression CJ Lin, RC Weng, SS Keerthi Journal of Machine Learning Research 9 (Apr), 627-650, 2008	617*	2008
Combining active learning and semi-supervised learning using gaussian fields and harmonic functions X Zhu, J Lafferty, Z Ghahramani ICML 2003 workshop on the continuum from labeled to unlabeled data in …, 2003	561	2003
A fast iterative nearest point algorithm for support vector machine classifier design SS Keerthi, SK Shevade, C Bhattacharyya, KRK Murthy IEEE transactions on neural networks 11 (1), 124-136, 2000	505	2000
A simple and efficient algorithm for gene selection using sparse logistic regression SK Shevade, SS Keerthi Bioinformatics 19 (17), 2246-2253, 2003	475	2003
Optimization techniques for semi-supervised support vector machines O Chapelle, V Sindhwani, SS Keerthi Journal of Machine Learning Research 9 (Feb), 203-233, 2008	466	2008
Efficient tuning of SVM hyperparameters using radius/margin bound and iterative algorithms SS Keerthi IEEE Transactions on Neural Networks 13 (5), 1225-1229, 2002	419	2002
Convergence of a generalized SMO algorithm for SVM classifier design SS Keerthi, EG Gilbert Machine Learning 46 (1-3), 351-360, 2002	412	2002
Building support vector machines with reduced classifier complexity SS Keerthi, O Chapelle, D DeCoste Journal of Machine Learning Research 7 (Jul), 1493-1515, 2006	358	2006
A modified finite Newton method for fast solution of large scale linear SVMs SS Keerthi, D DeCoste Journal of Machine Learning Research 6 (Mar), 341-361, 2005	341	2005
New approaches to support vector ordinal regression W Chu, SS Keerthi Proceedings of the 22nd international conference on Machine learning, 145-152, 2005	330	2005
Support vector ordinal regression W Chu, SS Keerthi Neural computation 19 (3), 792-815, 2007	301	2007
Large scale semi-supervised linear SVMs V Sindhwani, SS Keerthi Proceedings of the 29th annual international ACM SIGIR conference on …, 2006	299	2006

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