Sathiya Keerthi Selvaraj

Cytowane przez

	Wszystkie	Od 2020
Cytowania	24088	5427
h-indeks	51	33
i10-indeks	103	61

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Współautorzy

Shirish ShevadeIndian Institute of ScienceZweryfikowany adres z csa.iisc.ernet.in
Chong Jin OngAssociate Professor of Mechanical Engineering, National University of SingaporeZweryfikowany adres z nus.edu.sg
Elmer GilbertProfessor of EngineeringZweryfikowany adres z umich.edu
Wei Chu（褚崴）InfZweryfikowany adres z gatsby.ucl.ac.uk
Chih-Jen LinDistinguished professor, National Taiwan University and affiliated professor, MBZUAIZweryfikowany adres z csie.ntu.edu.tw
Olivier ChapelleGoogleZweryfikowany adres z chapelle.cc
Chiranjib BhattacharyyaProfessor, Indian Institute of ScienceZweryfikowany adres z csa.iisc.ernet.in
Radha Krishna Murthy KaruturiDirector of Research Data & Analytics, Center for Health Systems Research, Sutter HealthZweryfikowany adres z sutterhealth.org
Vikas SindhwaniGoogle DeepMind RoboticsZweryfikowany adres z google.com
Dhruv MahajanDistinguished Scientist, Llama, Meta AIZweryfikowany adres z fb.com
Dennis DeCosteAppleZweryfikowany adres z apple.com
Cho-Jui HsiehUniversity of California, Los AngelesZweryfikowany adres z cs.ucla.edu
Kai-Wei ChangAssociate Professor, UCLAZweryfikowany adres z kwchang.net
Balaraman RavindranProfessor of Computer Science, Indian Institute of Technology MadrasZweryfikowany adres z cse.iitm.ac.in
Johannes GehrkeMicrosoftZweryfikowany adres z microsoft.com
Ruby Chiu-Hsing WengProfessor of Statistics, National Chengchi UniversityZweryfikowany adres z nccu.edu.tw
Pranjul YadavMachine Learning, GoogleZweryfikowany adres z google.com
Khoa D DoanVinUniversityZweryfikowany adres z vinuni.edu.vn
Magdalena BalazinskaUniversity of WashingtonZweryfikowany adres z cs.washington.edu
Heow Pueh LeeMechanical Engineering, National University of SingaporeZweryfikowany adres z nus.edu.sg

Obserwuj

Sathiya Keerthi Selvaraj

Principal Staff Scientist @ LinkedIn, Mountain View

Zweryfikowany adres z linkedin.com - Strona główna

Optimization Machine Learning Learning with Structured Outputs Kernel Methods SVMs


Tytuł Sortuj wg cytatów Sortuj wg roku Sortuj wg tytułu	Cytowane przez Cytowane przez	Rok
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	2543	2001
Asymptotic behaviors of support vector machines with Gaussian kernel SS Keerthi, CJ Lin Neural computation 15 (7), 1667-1689, 2003	2418	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	1291	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	1230	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	1126	1988
Which is the best multiclass SVM method? An empirical study KB Duan, SS Keerthi International workshop on multiple classifier systems, 278-285, 2005	948	2005
Evaluation of simple performance measures for tuning SVM hyperparameters K Duan, SS Keerthi, AN Poo Neurocomputing 51, 41-59, 2003	939	2003
Trust region Newton method for large-scale logistic regression. CJ Lin, RC Weng, SS Keerthi Journal of Machine Learning Research 9 (4), 2008	744	2008
Optimization techniques for semi-supervised support vector machines. O Chapelle, V Sindhwani, SS Keerthi Journal of Machine Learning Research 9 (2), 2008	593	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	488	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	450	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	420	2005
New approaches to support vector ordinal regression W Chu, SS Keerthi Proceedings of the 22nd international conference on Machine learning, 145-152, 2005	399	2005
Support vector ordinal regression W Chu, SS Keerthi Neural computation 19 (3), 792-815, 2007	394	2007
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	385	2006
Efficient algorithms for ranking with SVMs O Chapelle, SS Keerthi Information retrieval 13, 201-215, 2010	344	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	335	1987

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