Prateek Jain

Researcher, Microsoft Research Adjunct Faculty, IIT Kanpur
Contact: 
I am a member of the Machine Learning and Optimization and the Algorithms and Data Sciences Group at Microsoft Research, Bangalore, India. My research interests are in machine learning, statistical learning theory, and optimization algorithms in general. I am also interested in applications of machine learning to privacy, computer vision, text mining and natural language processing.
Earlier, I completed my PhD at the University of Texas at Austin under Prof. Inderjit S. Dhillon.
Projects:

Matrix Completion

Compressive Sensing

Distance Metric Learning
Publications:
 S. Bhojanapalli, P. Jain, S. Sanghavi. Tighter Lowrank Approximation via Sampling the Leveraged Element. To appear, SODA 2015.
 D. Chakrabarty, P. Jain, P. Kothari. Provable Submodular Minimization using Wolfe's Algorithm. To appear, NIPS 2014 (oral presentation).
 P. Jain, A. Tewari, P. Kar. On Iterative Hard Thresholding Methods for Highdimensional MEstimation.To appear, NIPS 2014.
 H. Narasimhan, P. Kar, P. Jain. Online and Stochastic Gradient methods for Nondecomposable Loss Functions. To appear, NIPS 2014.
 P. Netrapalli, U N Niranjan, A. Anandkumar, S. Sanghavi, P. Jain. Nonconvex Robust PCA. To appear, NIPS 2014.
 P. Jain, S. Oh, Provable Tensor Factorization with Missing Data. To appear, NIPS 2014.
 S. Vijayanarasimhan, P. Jain, K. Grauman, Hashing Hyperplane Queries to Near Points with Applications to LargeScale Active Learning. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), 2014.
 P. Jain, S. Oh, Learning Mixtures of Discrete Product Distributions using Spectral Decompositions. COLT 2014.
 A. Agarwal, A. Anandkumar, P. Jain, P. Netrapalli, R. Tandon, Learning Sparsely Used Overcomplete Dictionaries via Alternating Minimization. COLT 2014.
 S. Bhojanapalli, P. Jain, Universal Matrix Completion. ICML 2014.
 P. Jain, A. G. Thakurta, (Near) Dimension Independent Risk Bounds for Differentially Private Learning. ICML 2014. (supplementary)
 H. Yu, P. Kar, P. Jain, I. S. Dhillon, Largescale Multilabel Learning with Missing Labels. ICML 2014. (supplementary)
 P. Jain, I. S. Dhillon, Provable Inductive Matrix Completion. Arxiv Preprint, 2013.
 Y. Mitgliakis, C. Caramanis, P. Jain, Memory Limited, Streaming PCA. NIPS 2013.
 P. Netrapalli, P. Jain, S. Sanghavi, Phase Retrieval using Alternating Minimization. NIPS 2013.
 P. Jain, A. Thakurta, Differentially Private Learning with Kernels. ICML 2013.
 S. Gopi, P. Netrapalli, P. Jain, A. Nori, Onebit Compressed Sensing. ICML 2013.
 P. Kar, B. Sriperumbudur, P. Jain, H. Karnick, On the Generalization Ability of Online Learning Algorithms for Pairwise Loss Functions. ICML 2013.
 P. Jain, P. Netrapalli, S. Sanghavi, Lowrank Matrix Completion using Alternating Minimization. STOC 2013.
 A. Nath, S. Mukherjee, P. Jain, N. Goyal, S. Laxman, Ad Impression Forecasting for Sponsored Search. WWW 2013.
 P. Kar, P. Jain, Supervised Learning with Similarity Functions. NIPS 2012.
 A. Kapoor, R. Viswanathan, P. Jain, Multilabel Classification using Bayesian Compressed Sensing. NIPS 2012.
 P. Jain, A. Thakurta, Mirror Descent based Interactive Database Privacy. RANDOM 2012.
 P. Jain, P. Kothari, A. Thakurta, Differentially Private Online Learning. COLT 2012.
 R. Viswanathan, P. Jain, S. Laxman, A. Arasu. A Learning Framework for SelfTuning Histograms. Arxiv: 1111.7925, 2011.
 P. Kar, P. Jain. Similaritybased Learning via Data driven Embeddings. In Proceedings, NIPS 2011.
 P. Jain, A. Tewari, I. S. Dhillon. Orthogonal Matching Pursuit with Replacement. In Proceedings, NIPS 2011. (arxiv preprint)
 P. Jain, B. Kulis, J. V. Davis, I. S. Dhillon. Metric and Kernel Learning using a Linear Transformation. Journal of Machine Learning (JMLR).
 P. Jain, B. Kulis, I. S. Dhillon. Inductive Regularized Learning of Kernel Functions. NIPS 2010. (supplementary material)
 P. Jain, R. Meka, I. S. Dhillon. Guaranteed Rank Minimization via Singular Value Projection. NIPS 2010. (supplementary material) source code
 P. Jain, S. Vijaynarasimhan, K. Grauman. Hashing Hyperplane Queries to Near Points with Applications to LargeScale Active Learning. NIPS 2010. (supplementary material)
 S. Vijaynarasimhan, P. Jain, K. Grauman. FarSighted Active Learning on a Budget for Image and Video Recognition. Proc. the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2010.
 P. Jain, B. Kulis, J. V. Davis, I. S. Dhillon. Metric and Kernel Learning using a Linear Transformation. Arxiv:0910.5932, 2009.
 R. Meka, P. Jain, I. S. Dhillon. Matrix Completion from PowerLaw Distributed Samples. Proc. the Advances in Neural Information Processing Systems (NIPS), 2009.
 B. Kulis, P. Jain, K. Grauman. Fast Image Search for Learned Metrics. Proc. the IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI),2009.
 Z. Lu, P. Jain, I. S. Dhillon. Geometry aware Metric Learning. Proc. the International Conference on Machine Learning (ICML), 2009.
 P. Jain, A. Kapoor. Active Learning for Large Multiclass Problems. Proc. the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2009. source code
 P. Jain, B. Kulis, I. S. Dhillon, K. Grauman. Online Metric Learning and Fast Similarity Search. Proc. the Advances in Neural Information Processing Systems (NIPS), 2008. (oral presentation)(longer version)
 R. Meka, P. Jain, C. Caramanis, I. S. Dhillon. Rank Minimization via Online Learning. Proc. the International Conference on Machine Learning, 2008.
 P. Jain, B. Kulis, K. Grauman. Fast Image Search for Learned Metrics. Proc. the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2008.(CVPR 2008 Best Student Paper Award)
 P. Jain, R. Meka, I. S. Dhillon. Simultaneous Unsupervised Learning of Disparate Clusterings. Proc. the SIAM Conference on Data Mining, 2008. (Best Paper RunnerUp Award)
Invited to appear in a special issue of Statistical Analysis and Data Mining.  P. Jain, B. Kulis, K. Grauman. Fast Similarity Search for Learned Metrics. UTCS Technical Report #TR0748, September, 2007.
 J. Davis, B. Kulis, P. Jain, S. Sra, I. Dhillon. Informationtheoretic Metric Learning. Proc. 24th International Conference on Machine Learning, 2007. (ICML 2007 Student Paper Award) source code
 P. Jain, B. Kulis, I. Dhillon. Online Linear Regression using Burg Entropy. UTCS Technical Report #TR0708, February, 2007.