Sathiya Keerthi Selvaraj

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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 SindhwaniRobotics at Google, New YorkVerified email at google.com
Dhruv MahajanResearch Scientist at Computer Vision Group, Facebook AIVerified email at fb.com
Cho-Jui HsiehUniversity of California, Los AngelesVerified email at cs.ucla.edu
Kai-Wei ChangAssociate Professor, UCLAVerified email at kwchang.net
Dennis DeCosteAppleVerified email at apple.com
Johannes GehrkeMicrosoftVerified email at microsoft.com
Balaraman RavindranProfessor of Computer Science, Indian Institute of Technology MadrasVerified email at cse.iitm.ac.in
Ruby Chiu-Hsing WengProfessor of Statistics, National Chengchi UniversityVerified email at nccu.edu.tw
Heow Pueh LeeMechanical Engineering, National University of SingaporeVerified email at nus.edu.sg
Pranjul YadavMachine Learning, GoogleVerified email at google.com
Magdalena BalazinskaUniversity of WashingtonVerified email at cs.washington.edu

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	2287	2001
Asymptotic behaviors of support vector machines with Gaussian kernel SS Keerthi, CJ Lin Neural computation 15 (7), 1667-1689, 2003	2206	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	1734	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	1154	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	1109	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	1068	1988
Which is the best multiclass SVM method? An empirical study KB Duan, SS Keerthi International workshop on multiple classifier systems, 278-285, 2005	860	2005
Evaluation of simple performance measures for tuning SVM hyperparameters K Duan, SS Keerthi, AN Poo Neurocomputing 51, 41-59, 2003	837	2003
Trust region Newton method for large-scale logistic regression. CJ Lin, RC Weng, SS Keerthi Journal of Machine Learning Research 9 (4), 2008	676	2008
Optimization techniques for semi-supervised support vector machines. O Chapelle, V Sindhwani, SS Keerthi Journal of Machine Learning Research 9 (2), 2008	532	2008
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	532	2000
A simple and efficient algorithm for gene selection using sparse logistic regression SK Shevade, SS Keerthi Bioinformatics 19 (17), 2246-2253, 2003	526	2003
Convergence of a generalized SMO algorithm for SVM classifier design SS Keerthi, EG Gilbert Machine Learning 46 (1), 351-360, 2002	444	2002
Efficient tuning of SVM hyperparameters using radius/margin bound and iterative algorithms SS Keerthi IEEE Transactions on Neural Networks 13 (5), 1225-1229, 2002	437	2002
A modified finite Newton method for fast solution of large scale linear SVMs. SS Keerthi, D DeCoste, T Joachims Journal of Machine Learning Research 6 (3), 2005	389	2005
Building support vector machines with reduced classifier complexity. SS Keerthi, O Chapelle, D DeCoste, KP Bennett, E Parrado-Hernández Journal of Machine Learning Research 7 (7), 2006	371	2006
New approaches to support vector ordinal regression W Chu, SS Keerthi Proceedings of the 22nd international conference on Machine learning, 145-152, 2005	357	2005
Support vector ordinal regression W Chu, SS Keerthi Neural computation 19 (3), 792-815, 2007	341	2007
Efficient algorithms for ranking with SVMs O Chapelle, SS Keerthi Information retrieval 13 (3), 201-215, 2010	328	2010
Computation of minimum-time feedback control laws for discrete-time systems with state-control constraints S Keerthi, E Gilbert IEEE Transactions on Automatic Control 32 (5), 432-435, 1987	322	1987

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