Cornell University
Dept of Computer Science
Upson Hall 4114
Ithaca, NY 14850


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About me

I am a postdoctoral associate at the Department of Computer Science in Cornell University. I work with Thorsten Joachims and Bobby Kleinberg. I obtained my PhD from Columbia University. Before that, I obtained a master of engineering at the Indian Institute of Science in Bengaluru.

Publications

  • Large-Margin Learning of Submodular Summarization Models
    R. Sipos and P. K. Shivaswamy and T. Joachims; Conference of the European Chapter of the Association for Computational Linguistics (EACL), April 2012.

  • Multi-armed Bandit Problems with History
    P. K. Shivaswamy and T. Joachims; Conference on Artificial Intelligence and Statistics (AISTATS) , April 2012.

  • Learning to Diverisfy from Implicit Feedback
    K. Raman and P. K. Shivaswamy and T. Joachims; WSDM Workshop on Diversity in Document Retrieval, February 2012.

  • Online Learning with Preference Feedback
    P. K. Shivaswamy and T. Joachims; NIPS workshop on Choice Models and Preference Learning , December 2011.

  • Variance Penalizing AdaBoost
    P. K. Shivaswamy and T. Jebara; Neural Information Processing Systems (NIPS) , December 2011.

  • Structured Learning of Two-level Dynamic Rankings
    K. Raman, T. Joachims and P. K. Shivaswamy; Conference on Information and Knowledge Management (CIKM), October 2011. (The paper provided here is a longer version of the paper published at CIKM.)

  • Boosted Multi-task learning
    O. Chapele, P. K. Shivaswamy, S. Vadrevu, K. Weinberger, Y. Zhang and B. Tseng; Machine Learning Journal , December 2010.

  • Laplacian Spectrum Learning
    P. K. Shivaswamy and T. Jebara; European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD), September 2010. mosek implementation.

  • Multi-Task Learning for Boosting with Application to Web Search Ranking
    O. Chapelle, P. K. Shivaswamy, S. Vadrevu, K. Weinberger, Y. Zhang and B. Tseng; The 16th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), July 2010.

  • Empirical Bernstein Boosting
    P. K. Shivaswamy and T. Jebara; International Conference on Artificial Intelligence and Statistics (AISTATS), May 2010.

  • Maximum Relative Margin and Data-Dependent Regularization
    P. K. Shivaswamy and T. Jebara; Journal of Machine Learning Research (JMLR) 2010.

  • Structured Prediction with Relative Margin
    P. K. Shivaswamy and T. Jebara; International Conference on Machine Learning and Applications (ICMLA), December 2009.

  • Relative Margin Machines
    P. K. Shivaswamy and T. Jebara; In Advances in Neural Information Processing Systems (NIPS) 21, 2009. Matlab code (do write back to us if you see improvements on your applications with RMM)

  • A Support Vector Approach to Censored Targets
    P. K. Shivaswamy, W. Chu and M. Jansche; In proceedings of the International Conference on Data Mining (ICDM) 2007.

  • Ellipsoidal Kernel Machines
    P. K. Shivaswamy and T. Jebara ; In proceedings of the eleventh International Conference on Artificial Intelligence and Statistics (AISTATS) 2007.
    An addendum on Kernelized MVE.

  • Permutation Invariant SVMs
    P. K. Shivaswamy and T. Jebara ; In proceedings of the twenty third International Conference on Machine Learning (ICML) 2006.

  • Second Order Cone Programming approaches for handling Missing and Uncertain Data
    P. K. Shivaswamy, C. Bhattacharyya, A. Smola; Journal of Machine Learning Research 7 (Special Topic on Machine Learning and Optimization) 1283--1314, 2006.

  • A Second Order Cone Programming Formulation for Classifying Missing Data
    C. Bhattacharyya, P. K. Shivaswamy and A. Smola; In Advances in Neural Information Processing Systems (NIPS) 17 2005.