Sathiya Keerthi Selvaraj

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Medförfattare

Shirish ShevadeIndian Institute of ScienceVerifierad e-postadress på csa.iisc.ernet.in
Elmer GilbertProfessor of EngineeringVerifierad e-postadress på umich.edu
Chong Jin OngAssociate Professor of Mechanical Engineering, National University of SingaporeVerifierad e-postadress på nus.edu.sg
Wei Chu（褚崴）InfVerifierad e-postadress på gatsby.ucl.ac.uk
Chih-Jen LinDistinguished professor, National Taiwan University and affiliated professor, MBZUAIVerifierad e-postadress på csie.ntu.edu.tw
Olivier ChapelleGoogleVerifierad e-postadress på chapelle.cc
Chiranjib BhattacharyyaProfessor, Indian Institute of ScienceVerifierad e-postadress på csa.iisc.ernet.in
Radha Krishna Murthy KaruturiDirector of Research Data & Analytics, Center for Health Systems Research, Sutter HealthVerifierad e-postadress på sutterhealth.org
Vikas SindhwaniGoogle DeepMind RoboticsVerifierad e-postadress på google.com
Dhruv MahajanDistinguished Scientist, Llama, Meta AIVerifierad e-postadress på fb.com
Dennis DeCosteAppleVerifierad e-postadress på apple.com
Cho-Jui HsiehUniversity of California, Los AngelesVerifierad e-postadress på cs.ucla.edu
Kai-Wei ChangAssociate Professor, UCLAVerifierad e-postadress på kwchang.net
Balaraman RavindranProfessor of Data Science and AI, Wadhwani School of Data Science and AI, IIT MadrasVerifierad e-postadress på dsai.iitm.ac.in
Johannes GehrkeMicrosoftVerifierad e-postadress på microsoft.com
Ruby Chiu-Hsing WengProfessor of Statistics, National Chengchi UniversityVerifierad e-postadress på nccu.edu.tw
Pranjul YadavMachine Learning, GoogleVerifierad e-postadress på google.com
Khoa D DoanVinUniversityVerifierad e-postadress på vinuni.edu.vn
Magdalena BalazinskaUniversity of WashingtonVerifierad e-postadress på cs.washington.edu
Heow Pueh LeeMechanical Engineering, National University of SingaporeVerifierad e-postadress på nus.edu.sg

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Sathiya Keerthi Selvaraj

Principal Staff Scientist @ LinkedIn, Mountain View

Verifierad e-postadress på linkedin.com - Startsida

Optimization Machine Learning Learning with Structured Outputs Kernel Methods SVMs


Titel Sortera efter citat Sortera efter år Sortera efter titel	Citeras av Citeras av	År
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	2540	2001
Asymptotic behaviors of support vector machines with Gaussian kernel SS Keerthi, CJ Lin Neural computation 15 (7), 1667-1689, 2003	2411	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	2033	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	1304	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	1232	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, 265-293, 1988	1133	1988
Which is the best multiclass SVM method? An empirical study KB Duan, SS Keerthi International workshop on multiple classifier systems, 278-285, 2005	947	2005
Evaluation of simple performance measures for tuning SVM hyperparameters K Duan, SS Keerthi, AN Poo Neurocomputing 51, 41-59, 2003	941	2003
Trust region Newton method for large-scale logistic regression. CJ Lin, RC Weng, SS Keerthi Journal of Machine Learning Research 9 (4), 2008	740	2008
Optimization techniques for semi-supervised support vector machines. O Chapelle, V Sindhwani, SS Keerthi Journal of Machine Learning Research 9 (2), 2008	592	2008
A simple and efficient algorithm for gene selection using sparse logistic regression SK Shevade, SS Keerthi Bioinformatics 19 (17), 2246-2253, 2003	590	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	561	2000
Convergence of a generalized SMO algorithm for SVM classifier design SS Keerthi, EG Gilbert Machine Learning 46, 351-360, 2002	487	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	452	2002
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	421	2005
New approaches to support vector ordinal regression W Chu, SS Keerthi Proceedings of the 22nd international conference on Machine learning, 145-152, 2005	406	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	392	2006
Support vector ordinal regression W Chu, SS Keerthi Neural computation 19 (3), 792-815, 2007	387	2007
Efficient algorithms for ranking with SVMs O Chapelle, SS Keerthi Information retrieval 13, 201-215, 2010	341	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, 2003	338	2003

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