Articles

Refereed Conference Publications

  1. Scalable Optimization of Multivariate Performance Measures in Multi-instance Multi-label Learning,
    Apoorv Aggarwal, Sandip Ghoshal, Ankith M S, Suhit Sinha, Ganesh Ramakrishnan, P. K., and Prateek Jain.
    31st AAAI Conference on Artificial Intelligence (AAAI), 2017.
    [pdf]

  2. Optimizing the Multiclass F-measure via Biconcave Programming,
    Weiwei Pan, Harikrishna Narasimhan, P.K., Pavlos Protopapas, and Harish G. Ramaswamy,
    16th IEEE International Conference on Data Mining (ICDM), 2016.
    [pdf]

  3. Stochastic Optimization Techniques for Quantification Performance Measures,
    P.K., Shuai Li, Harikrishna Narasimhan, Sanjay Chawla, and Fabrizio Sebastiani,
    22nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2016.
    arXiv : 1605.04135 [stat.ML], 2016.
    [pdf]

  4. Robust Regression via Hard Thresholding,
    Kush Bhatia, Prateek Jain, and P.K. ,
    29th Annual Conference on Neural Information Processing Systems (NIPS), 2015,
    Also at the IEEE Information Theory Workshop (ITW), October 11-15, 2015 (Invited Paper).
    Also at the NIPS Workshop on Non-convex Optimization for Machine Learning, December 11-12, 2015.
    arXiv : 1506.02428 [cs.LG], 2015.
    [pdf]

  5. Sparse Local Embeddings for Extreme Multi-label Classification,
    Kush Bhatia, Himanshu Jain, P.K., Manik Varma, and Prateek Jain,
    29th Annual Conference on Neural Information Processing Systems (NIPS), 2015,
    Also at the ICML Workshop on Extreme Classification, July 10, 2015.
    arXiv : 1507.02743 [cs.LG], 2015.
    [pdf]

  6. Surrogate Functions for Maximizing Precision at the Top,
    P. K., Harikrishna Narasimhan, and Prateek Jain,
    32nd International Conference on Machine Learning (ICML), 2015.
    Journal of Machine Learning Research (JMLR), W&CP, 37, 2015,
    arXiv: 1505.06813 [stat.ML], 2015.
    [pdf]

  7. Optimizing Non-decomposable Performance Measures: A Tale of Two Classes,
    Harikrishna Narasimhan, P. K., and Prateek Jain,
    32nd International Conference on Machine Learning (ICML), 2015.
    Journal of Machine Learning Research (JMLR), W&CP, 37, 2015,
    arXiv: 1505.06812 [stat.ML], 2015.
    [pdf]

  8. Online and Stochastic Gradient Methods for Non-decomposable Loss Functions,
    P. K., Harikrishna Narasimhan, and Prateek Jain,
    28th Annual Conference on Neural Information Processing Systems (NIPS), 2014,
    Also at the Symposium on Learning, Algorithms and Complexity (LAC), IISc, January 5-9, 2015,
    arXiv: 1410.6776 [cs.LG], 2014.
    [pdf]

  9. On Iterative Hard Thresholding Methods for High-dimensional M-Estimation,
    Prateek Jain, Ambuj Tewari, and P. K.,
    28th Annual Conference on Neural Information Processing Systems (NIPS), 2014,
    Also at the 22nd International Symposium on Mathematical Programming (ISMP), 2015,
    Also at the 7th NIPS Workshop on Optimization for Machine Learning (OPT), December 12-13, 2014,
    arXiv: 1410.5137 [cs.LG], 2014.
    [pdf]

  10. Large-scale Multi-label Learning with Missing Labels,
    Hsiang-Fu Yu, Prateek Jain, P. K., and Inderjit S. Dhillon,
    31st International Conference on Machine Learning (ICML), 2014,
    Journal of Machine Learning Research (JMLR), W&CP, 32(1):593-601, 2014,
    arXiv: 1307.5101 [cs.LG], 2013.
    [pdf]

  11. On the Generalization Ability of Online Learning Algorithms for Pairwise Loss Functions,
    P. K., Bharath Sriperumbudur, Prateek Jain, and Harish Karnick,
    30th International Conference on Machine Learning (ICML), 2013 (Oral Presentation),
    Journal of Machine Learning Research (JMLR), W&CP, 28(3):441-449, 2013,
    arXiv: 1305.2505 [cs.LG], 2013.
    [pdf]

  12. Supervised Learning with Similarity Functions,
    P. K. and Prateek Jain,
    26th Annual Conference on Neural Information Processing Systems (NIPS), 2012,
    arXiv: 1210.5840 [cs.LG], 2012.
    [pdf]

  13. Random Feature Maps for Dot Product Kernels,
    P. K. and Harish Karnick,
    15th International Conference on Artificial Intelligence and Statistics (AISTATS), 2012,
    Journal of Machine Learning Research (JMLR) : W&CP, 22:583-591, 2012,
    arXiv: 1201.6530 [cs.LG], 2012.
    [pdf]

  14. Similarity-based Learning via Data driven Embeddings,
    P. K. and Prateek Jain,
    25th Annual Conference on Neural Information Processing Systems (NIPS), 2011,
    arXiv: 1112.5404 [cs.LG], 2011.
    [pdf]

  15. Random Projection Trees Revisited,
    Aman Dhesi and P. K.,
    24th Annual Conference on Neural Information Processing Systems (NIPS), 2010,
    arXiv: 1010.3812 [cs.DS], 2010.
    [pdf]

  16. Estimating the First Frequency Moment of Data Streams in Nearly Optimal Space and Time,
    Sumit Ganguly and P. K.,
    12th Italian Conference on Theoretical Computer Science (ICTCS), 2010,
    arXiv: 1005.0809v1 [cs.DS], 2010.
    [pdf]

  17. On Low Distortion Embeddings of Statistical Distance Measures into Low Dimensional Spaces,
    Arnab Bhattacharya, P. K., and Manjish Pal,
    20th International Conference on Database and Expert Systems Applications (DEXA), 2009,
    Springer Lecture Notes in Computer Science (LNCS), 5690:164-172, 2009,
    arXiv: 0909.3169 [cs.CG], 2009.
    [pdf]

  18. INGIT: Limited Domain Formulaic Translation from Hindi to Indian Sign Language,
    P. K., Madhusudan Reddy, Amitabha Mukerjee, and Achla M Raina,
    5th International Conference on Natural Language Processing (ICON), pages 69-78, 2007.
    [pdf]

(Permanently) arXiv-ed articles

  1. On Translation Invariant Kernels and Screw Functions,
    P. K. and Harish Karnick,
    arXiv : 1302.4343 [math.FA], 2013.
    [pdf]

  2. Generalization Guarantees for a Binary Classification Framework for Two-Stage Multiple Kernel Learning,
    P. K.,
    arXiv : 1302.0406 [cs.LG], 2013.
    [pdf]

Un-refereed Publications

I contributed a couple of introductory articles to a student-led publication called NERD (Notes on Engineering Research and Development) [url].

  1. Why we respect our Teachers : A Note on Language Learnability and Active Learning,
    P. K.,
    Notes on Engineering Research and Development, 3(3):31-36, 2011.
    [pdf]

  2. Learning with Supportive Vectors : An Introduction to Support Vector Machines and their Applications,
    P. K.,
    Notes on Engineering Research and Development, 3(1):2-6, 2010.
    [pdf]

Miscellaneous

  1. The Ultra Experience of a non-Athlete,
    An article on how I came to participate in an ultra marathon.
    P. K.,
    2010.
    [pdf]