Shirish Shevade

Courses Taught

• Data Mining
• Pattern Recognition
• Topics in Pattern Recognition
• Computational Methods of Optimization
• Convex Optimization
• Linear and Nonlinear Optimization

Publications

Journal Papers

1. I. Sathish Reddy, Shirish Shevade and M. N. Murty, A fast Quasi-Newton method for semi-supervised SVM. Pattern Recognition, pp. 2305-2313, 2011.

2. Shirish Shevade and S. Sundararajan, Validation Based Sparse Gaussian Process Classifier Design, Neural Computation, 21(7), pp. 2082-2103, 2009.

3. S. Sathiya Keerthi and Shirish Shevade, A Fast Tracking Algorithm for Generalized LARS/LASSO, IEEE Transactions on Neural Networks, 19(6), pp. 1826-1830, 2007.

4. S. Sundararajan, Shirish Shevade, S. S. Keerthi, Fast generalized cross validation algorithm for sparse model learning, Neural Computation, 19(1), pp. 283-301, 2007.

5. J. Saketha Nath and S. K. Shevade, An efficient clustering scheme using support vector methods, Pattern Recognition, 39(8), pp. 1473-1480, 2006.

6. S. Asharaf, M. Narasimha Murty, and S.K. Shevade, Rough set based incremental clustering of interval data, Pattern Recognition Letters, 27, pp. 515-519, 2006.

7. Nam SW, Park JY, Ramasamy A, Shevade S, et al, Molecular changes from dysplastic nodule to hepatocellular carcinoma through gene expression profiling, Hepatology, 42, pp. 809-818, 2005.

8. S. Asharaf, S.K. Shevade, and M. Narasimha Murty, Rough support vector clustering, Pattern Recognition, 38, pp. 1779-1783, 2005.

9. S.S. Keerthi, K. Duan, S.K. Shevade, and A.N. Poo, A fast dual algorithm for kernel logistic regression, Machine Learning, 61(1-3), pp. 151-165, 2005.

10. S.K. Shevade and S.S. Keerthi, A simple and efficient algorithm for gene selection using sparse logistic regression, Bioinformatics, 19(17), pp. 2246-2253, 2003. Software

11. Keerthi S. S. and Shevade S. K., SMO algorithm for least squares SVM formulations. Neural Computation, 15(2), pp. 487-507, 2003.

12. Keerthi S. S., Shevade S. K., Bhattacharyya C. and Murthy K. R. K., Improvements to Platt's SMO algorithm for SVM classifier design. Neural Computation, 13(3), pp. 637-649, 2001.

13. Shevade S. K., Keerthi S. S., Bhattacharyya C. and Murthy K. R. K., Improvements to SMO algorithm for SVM regression. IEEE Transactions on Neural Networks, 11(5), pp. 1188-1194, 2000.

14. Keerthi S. S., Shevade S. K., Bhattacharyya C. and Murthy K. R. K., A fast iterative nearest point algorithm for support vector machine classifier design. IEEE Transactions on Neural Networks, 11(1), 124-136, 2000.

Conference Papers

1. S. Sathiya Keerthi, Bigyan Bhar, S. Sundararajan and Shirish Shevade, Semi-Supervised SVMs for Classification with Unknown Class Proportions and a Small Labeled Dataset. 20th ACM Conference on Information and Knowledge Management (CIKM), 2011.

2. P. Balamurugan, Shirish Shevade, S. Sundararajan and S. Sathiya Keerthi, A Sequential Dual Method for Structural SVMs. SIAM International Conference on Data Mining (SDM), 2011.

3. Dinesh Garg, S. Sundararajan and Shirish Shevade, A Game Theoretic Approach for Feature Clustering and Its Application to Feature Selection. Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2011.

4. Amrish Patel, S. Sundararajan and Shirish Shevade, Semi-supervised Classification using Sparse Gaussian Process Regression, International Joint conference on Artificial Intelligence (IJCAI), 2009.

5. S. Asharaf, M. Narasimha Murty, and S.K. Shevade, Multiclass Core Vector Machine, International Conference on Machine Learning (ICML), 2007.

6. S. K. Shevade and W. Chu, Minimum Enclosing Spheres Formulations for Support Vector Ordinal Regression, IEEE International Conference on Data Mining ( ICDM), 2006.

7. S. Asharaf, M. Narasimha Murty, and S.K. Shevade, Cluster Based Core Vector Machine, IEEE International Conference on Data Mining ( ICDM), 2006.

8. S. Asharaf, S.K. Shevade, and M. Narasimha Murty, Scalable non-linear support vector machine using hierarchical clustering, International Conference on Pattern Recognition (ICPR), 2006.

9. J. Saketha Nath and S. K. Shevade, An efficient clustering scheme using support vector methods, Indian International conference on Artificial Intelligence (IICAI), 2005.

10. S.K. Shevade, S. Sundararajan and S.S. Keerthi, Predictive approaches for sparse model learning, International conference on Neural Information Processing (ICONIP), 2004.

11. S.S. Keerthi and S. K. Shevade, SMO algorithm for least squares SVM, International Joint Conference on Neural Networks (IJCNN), 2003.

12. Keerthi S. S., Kaibo D., Shevade S. K. and Poo A. N., A fast dual algorithm for kernel logistic regression, International Conference on Machine Learning (ICML), 2002.