S. Sathiya Keerthi

Sathiya Keerthi Selvaraj

	2012
71		Paramveer S. Dhillon, S. Sathiya Keerthi, Kedar Bellare, Olivier Chapelle, Sundararajan Sellamanickam: Deterministic Annealing for Semi-Supervised Structured Output Learning. Journal of Machine Learning Research - Proceedings Track 22: 299-307 (2012)
	2011
70		Sathiya Keerthi Selvaraj, Bigyan Bhar, Sundararajan Sellamanickam, Shirish Krishnaj Shevade: Semi-supervised SVMs for classification with unknown class proportions and a small labeled dataset. CIKM 2011: 653-662
69		Sundararajan Sellamanickam, Priyanka Garg, Sathiya Keerthi Selvaraj: A pairwise ranking based approach to learning with positive and unlabeled examples. CIKM 2011: 663-672
68		Paramveer S. Dhillon, Sundararajan Sellamanickam, Sathiya Keerthi Selvaraj: Semi-supervised multi-task learning of structured prediction models for web information extraction. CIKM 2011: 957-966
67		Shirish Krishnaj Shevade, Balamurugan P., S. Sundararajan, S. Sathiya Keerthi: A Sequential Dual Method for Structural SVMs. SDM 2011: 223-234
66		Chiru Bhattacharyya, S. Sathiya Keerthi: Mean Field Methods for a Special Class of Belief Networks CoRR abs/1106.0246: (2011)
	2010
65		Olivier Chapelle, S. Sathiya Keerthi: Efficient algorithms for ranking with SVMs. Inf. Retr. 13(3): 201-215 (2010)
	2008
64		Cho-Jui Hsieh, Kai-Wei Chang, Chih-Jen Lin, S. Sathiya Keerthi, S. Sundararajan: A dual coordinate descent method for large-scale linear SVM. ICML 2008: 408-415
63		S. Sathiya Keerthi, S. Sundararajan, Kai-Wei Chang, Cho-Jui Hsieh, Chih-Jen Lin: A sequential dual method for large scale multi-class linear svms. KDD 2008: 408-416
62		Olivier Chapelle, Vikas Sindhwani, S. Sathiya Keerthi: Optimization Techniques for Semi-Supervised Support Vector Machines. Journal of Machine Learning Research 9: 203-233 (2008)
61		Chih-Jen Lin, Ruby C. Weng, S. Sathiya Keerthi: Trust Region Newton Method for Logistic Regression. Journal of Machine Learning Research 9: 627-650 (2008)
	2007
60		Chih-Jen Lin, Ruby C. Weng, S. Sathiya Keerthi: Trust region Newton methods for large-scale logistic regression. ICML 2007: 561-568
59		Vikas Sindhwani, Wei Chu, S. Sathiya Keerthi: Semi-Supervised Gaussian Process Classifiers. IJCAI 2007: 1059-1064
58		S. Sathiya Keerthi, John A. Tomlin: Constructing a maximum utility slate of on-line advertisements CoRR abs/0706.1318: (2007)
57		S. Sathiya Keerthi, Shirish Krishnaj Shevade: A Fast Tracking Algorithm for Generalized LARS/LASSO. IEEE Transactions on Neural Networks 18(6): 1826-1830 (2007)
56		S. Sundararajan, Shirish Krishnaj Shevade, S. Sathiya Keerthi: Fast Generalized Cross-Validation Algorithm for Sparse Model Learning. Neural Computation 19(1): 283-301 (2007)
55		Wei Chu, S. Sathiya Keerthi: Support Vector Ordinal Regression. Neural Computation 19(3): 792-815 (2007)
	2006
54		Vikas Sindhwani, S. Sathiya Keerthi, Olivier Chapelle: Deterministic annealing for semi-supervised kernel machines. ICML 2006: 841-848
53		Olivier Chapelle, Vikas Sindhwani, S. Sathiya Keerthi: Branch and Bound for Semi-Supervised Support Vector Machines. NIPS 2006: 217-224
52		Wei Chu, Vikas Sindhwani, Zoubin Ghahramani, S. Sathiya Keerthi: Relational Learning with Gaussian Processes. NIPS 2006: 289-296
51		S. Sathiya Keerthi, Vikas Sindhwani, Olivier Chapelle: An Efficient Method for Gradient-Based Adaptation of Hyperparameters in SVM Models. NIPS 2006: 673-680
50		Vikas Sindhwani, S. Sathiya Keerthi: Large scale semi-supervised linear SVMs. SIGIR 2006: 477-484
49		L. J. Cao, S. Sathiya Keerthi, Chong Jin Ong, J. Q. Zhang, U. Periyathamby, Xiu Ju Fu, H. P. Lee: Parallel sequential minimal optimization for the training of support vector machines. IEEE Transactions on Neural Networks 17(4): 1039-1049 (2006)
48		S. Sathiya Keerthi, Olivier Chapelle, Dennis DeCoste: Building Support Vector Machines with Reduced Classifier Complexity. Journal of Machine Learning Research 7: 1493-1515 (2006)
47		L. J. Cao, S. Sathiya Keerthi, Chong Jin Ong, P. Uvaraj, Xiu Ju Fu, H. P. Lee: Developing parallel sequential minimal optimization for fast training support vector machine. Neurocomputing 70(1-3): 93-104 (2006)
	2005
46		Wei Chu, S. Sathiya Keerthi: New approaches to support vector ordinal regression. ICML 2005: 145-152
45		S. Sathiya Keerthi: Generalized LARS as an effective feature selection tool for text classification with SVMs. ICML 2005: 417-424
44		Kaibo Duan, S. Sathiya Keerthi: Which Is the Best Multiclass SVM Method? An Empirical Study. Multiple Classifier Systems 2005: 278-285
43		S. Sathiya Keerthi, Wei Chu: A matching pursuit approach to sparse Gaussian process regression. NIPS 2005
42		Wei Chu, Chong Jin Ong, S. Sathiya Keerthi: An improved conjugate gradient scheme to the solution of least squares SVM. IEEE Transactions on Neural Networks 16(2): 498-501 (2005)
41		S. Sathiya Keerthi, Dennis DeCoste: A Modified Finite Newton Method for Fast Solution of Large Scale Linear SVMs. Journal of Machine Learning Research 6: 341-361 (2005)
40		S. Sathiya Keerthi, Kaibo Duan, Shirish Krishnaj Shevade, A. Poo: A Fast Dual Algorithm for Kernel Logistic Regression. Machine Learning 61(1-3): 151-165 (2005)
	2004
39		Shirish Krishnaj Shevade, S. Sundararajan, S. Sathiya Keerthi: Predictive Approaches for Sparse Model Learning. ICONIP 2004: 434-439
38		Chong Jin Ong, S. Sathiya Keerthi, Elmer G. Gilbert, Z. H. Zhang: Stability regions for constrained nonlinear systems and their functional characterization via support-vector-machine learning. Automatica 40(11): 1955-1964 (2004)
37		Wei Chu, S. Sathiya Keerthi, Chong Jin Ong: Bayesian support vector regression using a unified loss function. IEEE Transactions on Neural Networks 15(1): 29-44 (2004)
36		Martin M. S. Lee, S. Sathiya Keerthi, Chong Jin Ong, Dennis DeCoste: An efficient method for computing leave-one-out error in support vector machines with Gaussian kernels. IEEE Transactions on Neural Networks 15(3): 750-757 (2004)
	2003
35		Min Shi, David S. Edwin, Rakesh Menon, Lixiang Shen, Jonathan Y. K. Lim, Han Tong Loh, S. Sathiya Keerthi, Chong Jin Ong: A Machine Learning Approach for the Curation of Biomedical Literature. ECIR 2003: 597-604
34		Rakesh Menon, Han Tong Loh, S. Sathiya Keerthi, Aarnout Brombacher: Automated Text Classification for Fast Feedback - Investigating the Effects of Document Representation. KES 2003: 1008-1014
33		Kaibo Duan, S. Sathiya Keerthi, Wei Chu, Shirish Krishnaj Shevade, Aun Neow Poo: Multi-category Classification by Soft-Max Combination of Binary Classifiers. Multiple Classifier Systems 2003: 125-134
32		Shirish Krishnaj Shevade, S. Sathiya Keerthi: A simple and efficient algorithm for gene selection using sparse logistic regression. Bioinformatics 19(17): 2246-2253 (2003)
31		S. Sathiya Keerthi, Shirish Krishnaj Shevade: SMO Algorithm for Least-Squares SVM Formulation. Neural Computation 15(2): 487-507 (2003)
30		S. Sathiya Keerthi, Chih-Jen Lin: Asymptotic Behaviors of Support Vector Machines with Gaussian Kernel. Neural Computation 15(7): 1667-1689 (2003)
29		Wei Chu, S. Sathiya Keerthi, Chong Jin Ong: Bayesian Trigonometric Support Vector Classifier. Neural Computation 15(9): 2227-225 (2003)
28		Kaibo Duan, S. Sathiya Keerthi, Aun Neow Poo: Evaluation of simple performance measures for tuning SVM hyperparameters. Neurocomputing 51: 41-59 (2003)
27		Colin Campbell, Chih-Jen Lin, S. Sathiya Keerthi, V. David Sánchez A.: Special issue on support vector machines. Neurocomputing 55(1-2): 1-3 (2003)
	2002
26		S. Sathiya Keerthi, Kaibo Duan, Shirish Krishnaj Shevade, Aun Neow Poo: A Fast Dual Algorithm for Kernel Logistic Regression. ICML 2002: 299-306
25		S. Sathiya Keerthi: Efficient tuning of SVM hyperparameters using radius/margin bound and iterative algorithms. IEEE Transactions on Neural Networks 13(5): 1225-1229 (2002)
24		S. Sathiya Keerthi, Elmer G. Gilbert: Convergence of a Generalized SMO Algorithm for SVM Classifier Design. Machine Learning 46(1-3): 351-360 (2002)
23		S. Sathiya Keerthi, Chong Jin Ong, Keng Boon Siah, David B. L. Lim, Wei Chu, Min Shi, David S. Edwin, Rakesh Menon, Lixiang Shen, Jonathan Y. K. Lim, Han Tong Loh: A Machine Learning Approach for the Curation of Biomedical Literature - KDD Cup 2002 (Task 1). SIGKDD Explorations 4(2): 93-94 (2002)
	2001
22		Wei Chu, S. Sathiya Keerthi, Chong Jin Ong: A Unified Loss Function in Bayesian Framework for Support Vector Regression. ICML 2001: 51-58
21		Chiranjib Bhattacharyya, S. Sathiya Keerthi: Mean Field Methods for a Special Class of Belief Networks. J. Artif. Intell. Res. (JAIR) 15: 91-114 (2001)
20		S. Sathiya Keerthi, Shirish Krishnaj Shevade, Chiranjib Bhattacharyya, K. R. K. Murthy: Improvements to Platt's SMO Algorithm for SVM Classifier Design. Neural Computation 13(3): 637-649 (2001)
19		S. Sundararajan, S. Sathiya Keerthi: Predictive Approaches for Choosing Hyperparameters in Gaussian Processes. Neural Computation 13(5): 1103-1118 (2001)
18		K. R. K. Murthy, S. Sathiya Keerthi, M. Narasimha Murty: Rule prepending and post-pruning approach to incremental learning of decision lists. Pattern Recognition 34(8): 1697-1699 (2001)
	2000
17		Chiranjib Bhattacharyya, S. Sathiya Keerthi: A Variational Mean-Field Theory for Sigmoidal Belief Networks. NIPS 2000: 374-380
16		S. Sathiya Keerthi, Shirish Krishnaj Shevade, Chiranjib Bhattacharyya, K. R. K. Murthy: A fast iterative nearest point algorithm for support vector machine classifier design. IEEE Trans. Neural Netw. Learning Syst. 11(1): 124-136 (2000)
15		Shirish Krishnaj Shevade, S. Sathiya Keerthi, Chiranjib Bhattacharyya, K. R. K. Murthy: Improvements to the SMO algorithm for SVM regression. IEEE Trans. Neural Netw. Learning Syst. 11(5): 1188-1193 (2000)
14		G. Phanendra Babu, M. Narasimha Murty, S. Sathiya Keerthi: A stochastic connectionist approach for global optimization with application to pattern clustering. IEEE Transactions on Systems, Man, and Cybernetics, Part B 30(1): 10-24 (2000)
	1999
13		C. S. Sundaresan, S. Sathiya Keerthi: A Study of Representations for Pen based Handwriting Recognition of Tamil Characters. ICDAR 1999: 422-425
12		K. R. K. Murthy, S. Sathiya Keerthi: Context Filters for Document-based Information Filtering. ICDAR 1999: 709-712
11		S. Sathiya Keerthi, Chong Jin Ong, Eugene Huang, Elmer G. Gilbert: EquiDistance Diagram: A New Roadmap Method for Path Planning. ICRA 1999: 682-687
10		S. Sundararajan, S. Sathiya Keerthi: Predictive App roaches for Choosing Hyperparameters in Gaussian Processes. NIPS 1999: 631-637
	1998
9		Dipti Deodhare, M. Vidyasagar, S. Sathiya Keerthi: Synthesis of fault-tolerant feedforward neural networks using minimax optimization. IEEE Transactions on Neural Networks 9(5): 891-900 (1998)
	1995
8		Vijay Chandru, Abhi Dattasharma, S. Sathiya Keerthi, N. K. Sancheti, V. Vinay: Algorithms for the Optimal Loading of Recursive Neural Nets. SODA 1995: 342-349
7		Abhi Dattasharma, S. Sathiya Keerthi: An Augmented Voronoi Roadmap for 3D Translational Motion Planning for a Convex Polyhedron Moving Amidst Convex Polyhedral Obstacles. Theor. Comput. Sci. 140(2): 205-230 (1995)
	1994
6		K. Sridharan, Harry E. Stephanou, K. C. Craig, S. Sathiya Keerthi: Distance Measures on Intersecting Objects and Their Applications. Inf. Process. Lett. 51(4): 181-188 (1994)
	1993
5		Abhi Dattasharma, S. Sathiya Keerthi: Translational Motion Planning for a Convex Polyhedron in a 3D Polyhedral World Using an Efficient and New Roadmap. CCCG 1993: 449-454
4		Nukala V. R. K. N. Murthy, S. Sathiya Keerthi: Optimal Control of a Somersaulting Platform Diver: A Numerical Approach. ICRA (1) 1993: 1013-1018
3		K. Sridharan, Harry E. Stephanou, S. Sathiya Keerthi: On Computing a Distance Measure for Path Planning. ICRA (1) 1993: 554-559
2		Sudhaker Samuel, S. Sathiya Keerthi: Numerical Determination of Optimal Non-Holonomic Paths in the Presence of Obstacles. ICRA (1) 1993: 826-831
	1992
1		Makarand S. Phatak, S. Sathiya Keerthi: A homotopy approach for stabilizing single-input systems with control structure constraints. Automatica 28(5): 981-987 (1992)

Coauthor Index

1	V. David Sánchez A.	[27]
2	G. Phanendra Babu	[14]
3	Kedar Bellare	[71]
4	Bigyan Bhar	[70]
5	Chiranjib Bhattacharyya (Chiru Bhattacharyya)	[15] [16] [17] [20] [21] [66]
6	Aarnout Brombacher	[34]
7	Colin Campbell	[27]
8	L. J. Cao	[47] [49]
9	Vijay Chandru (Vijaya Chandru)	[8]
10	Kai-Wei Chang	[63] [64]
11	Olivier Chapelle	[48] [51] [53] [54] [62] [65] [71]
12	Wei Chu	[22] [23] [29] [33] [37] [42] [43] [46] [52] [55] [59]
13	K. C. Craig	[6]
14	Abhi Dattasharma	[5] [7] [8]
15	Dennis DeCoste	[36] [41] [48]
16	Dipti Deodhare	[9]
17	Paramveer S. Dhillon	[68] [71]
18	Kaibo Duan	[26] [28] [33] [40] [44]
19	David S. Edwin	[23] [35]
20	Xiu Ju Fu	[47] [49]
21	Priyanka Garg	[69]
22	Zoubin Ghahramani	[52]
23	Elmer G. Gilbert	[11] [24] [38]
24	Cho-Jui Hsieh	[63] [64]
25	Eugene Huang	[11]
26	H. P. Lee	[47] [49]
27	Martin M. S. Lee	[36]
28	David B. L. Lim	[23]
29	Jonathan Y. K. Lim	[23] [35]
30	Chih-Jen Lin	[27] [30] [60] [61] [63] [64]
31	Han Tong Loh	[23] [34] [35]
32	Rakesh Menon	[23] [34] [35]
33	K. R. K. Murthy	[12] [15] [16] [18] [20]
34	Nukala V. R. K. N. Murthy	[4]
35	M. Narasimha Murty	[14] [18]
36	Chong Jin Ong	[11] [22] [23] [29] [35] [36] [37] [38] [42] [47] [49]
37	Balamurugan P.	[67]
38	U. Periyathamby	[49]
39	Makarand S. Phatak	[1]
40	A. Poo	[40]
41	Aun Neow Poo	[26] [28] [33]
42	Sudhaker Samuel	[2]
43	N. K. Sancheti	[8]
44	Sundararajan Sellamanickam	[68] [69] [70] [71]
45	Lixiang Shen	[23] [35]
46	Shirish Krishnaj Shevade	[15] [16] [20] [26] [31] [32] [33] [39] [40] [56] [57] [67] [70]
47	Min Shi	[23] [35]
48	Keng Boon Siah	[23]
49	Vikas Sindhwani	[50] [51] [52] [53] [54] [59] [62]
50	K. Sridharan	[3] [6]
51	Harry E. Stephanou	[3] [6]
52	S. Sundararajan	[10] [19] [39] [56] [63] [64] [67]
53	C. S. Sundaresan	[13]
54	John A. Tomlin	[58]
55	P. Uvaraj	[47]
56	M. Vidyasagar	[9]
57	V. Vinay	[8]
58	Ruby C. Weng	[60] [61]
59	J. Q. Zhang	[49]
60	Z. H. Zhang	[38]

Colors in the list of coauthors

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