- Data Mining
- Optimization for Machine Learning
- Pattern Recognition
- Topics in Pattern Recognition
- Computational Methods of Optimization
- Convex Optimization
- Linear and Nonlinear Optimization

- P. Balamurugan, Shirish Shevade and S. Sundararajan, A Simple Label Switching Algorithm for Semi-supervised Structural SVMs.
**Neural Computation**, 27(10), pp. 2183-2206, 2015. - P. Balamurugan, Shirish Shevade and T. Ravindra Babu,
Scalable Sequential Alternating Proximal Methods for Sparse Structural SVMs
and CRFs.
**Knowledge and Information Systems**, 38(3), pp. 599-621, 2014. - I. Sathish Reddy, Shirish Shevade and M. N. Murty, A fast Quasi-Newton
method for semi-supervised SVM.
**Pattern Recognition**, pp. 2305-2313, 2011. - Shirish Shevade and S. Sundararajan, Validation Based Sparse Gaussian Process Classifier Design,
**Neural Computation**, 21(7), pp. 2082-2103, 2009. - 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. - S. Sundararajan, Shirish Shevade, S. S. Keerthi, Fast generalized cross
validation algorithm for sparse model learning,
**Neural Computation**, 19(1), pp. 283-301, 2007. - J. Saketha Nath and S. K. Shevade, An efficient clustering scheme using support vector methods,
**Pattern Recognition**, 39(8), pp. 1473-1480, 2006. - 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. - 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. - S. Asharaf, S.K. Shevade, and M. Narasimha Murty, Rough support vector clustering,
**Pattern Recognition**, 38, pp. 1779-1783, 2005. - 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. - 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 - Keerthi S. S. and Shevade S. K., SMO algorithm for least
squares SVM formulations.
**Neural Computation**, 15(2), pp. 487-507, 2003. - 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. - 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. - 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.

- Divya Padmanabhan, Satyanath Bhat, Shirish Shevade and
Y. Narahari,
Topic Model based Multi-Label Classification. IEEE International Conference on Tools with Artificial Intelligence (
**ICTAI**), 2016. - P.K. Srijith, P. Balamurugan and Shirish Shevade,
Gaussian Process Pseudo-Likelihood Models for Sequence Labeling. European Conference on Machine Learning and
Principles and Practice of Knowledge Discovery in Databases (
**ECML-PKDD**), 2016. - Divya Padmanabhan, Satyanath Bhat, Dinesh Garg, Shirish Shevade and
Y. Narahari,
A Robust UCB Scheme for Active Learning in Regression from Strategic
Crowds. International Joint Conference on Neural Networks (
**IJCNN**), 2016. - P. Balamurugan, Anusha Posinasetti and Shirish Shevade,
ADMM for Training Sparse Structural SVMs with Augmented $\ell_1$ Regularization,
SIAM International Conference on Data Mining (
**SDM**), 2016. - Goutham Tholpadi, Chiranjeeb Bhattacharyya and Shirish Shevade,
Translation Induction on Indian Language Corpora using
Translingual Themes from Other Languages. 16th International Conference on
Intelligent Text Processing and Computational Linguistics (
**CICLing**), 2015. - P.K. Srijith and Shirish Shevade, Gaussian Process Multi-Task
Learning Using Joint Feature Selection. European Conference on Machine Learning and
Principles and Practice of Knowledge Discovery in Databases (
**ECML-PKDD**), 2014. - P.K. Srijith, Shirish Shevade and S. Sundararajan, Semi-supervised Gaussian Process Ordinal Regression. European Conference on Machine Learning and
Principles and Practice of Knowledge Discovery in Databases (
**ECML-PKDD**), 2013. - Punya Murthy Chinta, Balamurugan Palaniappan, Shirish
Shevade and M. Narasimha Murty, Optimizing F-Measure with Non-Convex Loss and Sparse Linear Classifiers. International Joint Conference on Neural Networks (
**IJCNN**), 2013. - Tanuja Ganu, Shirish Shevade and S. Sundararajan, Sparse Max-Margin Multiclass and Multi-label Classifier Design
for Fast Inference. SIAM International Conference on Data Mining (
**SDM**), 2013. - S. Sathiya Keerthi, S. Sundararajan and Shirish Shevade,
Extension of TSVM to Multi-Class and Hierarchical Text Classification Problems With
General Losses. International Conference on Computational Linguistics (
**COLING**), 2012. - P. Balamurugan, Shirish Shevade, and T. Ravindra Babu,
A Sequential Alternating Proximal Method for Scalable Sparse Structural SVMs.
IEEE International Conference on Data
Mining (
**ICDM**), 2012. - P.K. Srijith, Shirish Shevade and S. Sundararajan, A Probabilistic Least Squares Approach to Ordinal Regression. Australasian Joint Conference on Artificial Intelligence (
**AI**), 2012. - P.K. Srijith and Shirish Shevade, Validation Based Sparse Gaussian Processes for Ordinal Regression. International Conference on
Neural Information Processing (
**ICONIP**), 2012. - P.K. Srijith, Shirish Shevade and S. Sundararajan, Validation Based Sparse Gaussian Processes for Ordinal Regression. International Conference on
Neural Information Processing (
**ICONIP**), 2012. - Sneha Chaudhari and Shirish Shevade, Learning from Positive and Unlabelled Examples using Maximum Margin Clustering.
International Conference on
Neural Information Processing (
**ICONIP**), 2012. - Dinesh Garg, S. Sundararajan, S. Bhattacharya and Shirish Shevade,
Mechanism Design for Cost Optimal PAC
Learning in the Presence of Strategic Noisy Annotators.
Uncertainty in Artificial Intelligence (
**UAI**), 2012. - P. Balamurugan, Shirish Shevade and Ravindra Babu T., Efficient Algorithms for Linear Summed Error Structural SVMs. International Joint Conference on Neural Networks (
**IJCNN**), 2012. - G. Tholpadi, M. K. Das, C. Bhattacharyya and S. Shevade, Cluster Labeling for Multilingual Scatter/Gather using
Comparable Corpora. European Conference on
Information Retrieval (
**ECIR**), 2012. - S. Sathiya Keerthi, Bigyan Bhar, Sundararajan S, and Shirish Shevade,
Semi-Supervised SVMs for Classification with Unknown Class Proportions and a Small Labeled Dataset. ACM Conference on
Information and Knowledge Management (
**CIKM**), 2011. - 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. - Dinesh Garg, S. Sundararajan, 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. - 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. - 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. Software - 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. - Amrish Patel, S. Sundararajan and Shirish Shevade, Semi-supervised
Classification using Sparse Gaussian Process Regression, International Joint conference on Artificial Intelligence (
**IJCAI**), 2009. - S. Asharaf, M. Narasimha Murty, and S.K. Shevade, Multiclass Core Vector Machine, International Conference on Machine Learning (
**ICML**), 2007. - S. K. Shevade and W. Chu, Minimum Enclosing Spheres Formulations for Support Vector Ordinal Regression, IEEE International Conference on Data Mining (
**ICDM**), 2006. - S. Asharaf, M. Narasimha Murty, and S.K. Shevade, Cluster Based Core Vector Machine, IEEE International Conference on Data Mining (
**ICDM**), 2006. - 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. - J. Saketha Nath and S. K. Shevade, An efficient clustering scheme using support vector methods, Indian International conference on Artificial Intelligence (
**IICAI**), 2005. - S.K. Shevade, S. Sundararajan and S.S. Keerthi, Predictive approaches for sparse model learning, International conference on
Neural Information Processing (
**ICONIP**), 2004. - S.S. Keerthi and S. K. Shevade, SMO algorithm for least squares SVM,
International Joint Conference on Neural Networks (
**IJCNN**), 2003. - 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.