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Conference Proceedings

Kasinikota, Anusha and Balamurugan, P and Shevade, Shirish (2018) Modeling Label Interactions in Multi-label Classification: A Multi-structure SVM Perspective. In: 22nd Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), JUN 03-06, 2018, Deakin Univ, Melbourne, AUSTRALIA, pp. 43-55.

Balamurugan, P (2013) Large-Scale Elastic Net Regularized Linear Classification SVMs and Logistic Regression. In: IEEE 13th International Conference on Data Mining (ICDM), DEC 07-10, 2013, Dallas, TX, pp. 949-954.

Chinta, Punya Murthy and Balamurugan, P and Shevade, Shirish and Murty, Narasimha M (2013) Optimizing F-Measure with Non-Convex Loss and Sparse Linear Classifiers. In: INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), AUG 04-09, 2013, Dallas, TX.

Balamurugan, P and Shevade, Shirish and Babu, Ravindra T (2012) Efficient Algorithms for Linear Summed Error Structural SVMs. In: IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)/International Joint Conference on Neural Networks (IJCNN)/IEEE Congress on Evolutionary Computation (IEEE-CEC)/IEEE World Congress on Computational Intelligence (IEEE-WCCI) , JUN 10-15, 2012 , Brisbane, AUSTRALIA.

Conference Paper

Balamurugan, P and Shevade, Shirish and Babu, Ravindra T (2012) Sequential alternating proximal method for scalable sparse structural SVMs. In: 2012 IEEE 12th International Conference on Data Mining (ICDM), 10-13 Dec. 2012, Brussels, BELGIUM, pp. 61-70.

Balamurugan, P and Shevade, Shirish and Sundararajan, S and Keerthi, Sathiya S (2011) A sequential dual method for structural SVMs. In: 2011 SIAM International Conference on Data Mining (SDM), April 28-30,2011, Mesa, Arizona, USA.

Journal Article

Balamurugan, P and Shevade, Shirish and Sundararajan, S (2015) A Simple Label Switching Algorithm for Semisupervised Structural SVMs. In: NEURAL COMPUTATION, 27 (10). pp. 2183-2206.

Balamurugan, P and Shevade, Shirish and Babu, Ravindra T (2014) Scalable sequential alternating proximal methods for sparse structural SVMs and CRFs. In: KNOWLEDGE AND INFORMATION SYSTEMS, 38 (3). pp. 599-621.