Prateek Jain at Microsoft Research

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, large-scale (non-convex optimization), and statistical learning theory. I am also interested in applications of machine learning to privacy, computer vision, text mining and natural language processing. I completed my PhD at the University of Texas at Austin under Prof. Inderjit S. Dhillon.

I am also an adjunct faculty member at IIT Kanpur.

Professional Services

Organization:
- Program Co-Chair, IKDD Conference on Data Sciences (CoDS), 2016.
- Organizer, Machine Learning Summer School, Microsoft Research, 2015.
- Organizer, Mysore Park Workshop on Machine Learning, Mysore, India, 2012.
Program Committee/Area Chair
- COLT 2015, 2016
- NIPS 2012, 2013, 2016

Students

Over the years, I have been very lucky to have worked with some amazing postdocs/interns/research fellows.

PostDocs:

Purushottam Kar, 2013-2015 (Asst. Prof., IIT Kanpur)
Nagarajan Natarajan, 2015- (Postdoc, MSR India)

Interns:

Elena-Madalina Persu, Summer’2015. (Phd Student, MIT)
Gautam Kamath, Summer’2015. (Phd Student, MIT)
Harikrishna Narasimhan, Summer’2014. (Postdoc, Harvard University)
Praneeth Netrapalli, Summer’2012, 2014. (Postdoc, Microsoft Research New England)
Srinadh Bhojanapalli, Summer’2013, 2014. (Assistant Professor, TTI Chicago)
Pravesh Kothari, Summer’2014. (Phd Student, UT Austin)
Purushottam Kar, Summer’2012. (Assistant Professor, IIT Kanpur)
Sivakanth Gopi, Summer’2012. (Phd Student, Princeton University)
Ankan Saha, Summer’2011. (Software Engineer, LinkedIn)
Saurabh Gupta, Summer’2011. (Phd Student, UC Berkeley)

Research Fellows:

Kush Bhatia, 2014-2016. (PhD Student, UC Berkeley)
Yeshwanth Cherapanamjeri, 2015-. (RF, MSR India)
Raajay Viswanathan, 2011-2013. (PhD Student, UWisc Madison)

Provable Non-convex Optimization for Machine Learning Problems

Established: April 4, 2014

In this work, we explore theoretical properties of simple non-convex optimization methods for problems that feature prominently in several important areas such as recommendation systems, compressive sensing, computer vision etc. Talks: Provable Non-convex Optimization for Machine Learning. Summer School on Non-convex Optimization, IIT Bombay, 2015. [part 1] [part 2] Iterative Hard Thresholding for Sparse/Low-rank Linear Regression. INRIA, France, 2015. [pdf version] Iterative Hard Thresholding for Robust Regression. ITW, 2015. [pdf version] Provable Alternating Minimization methods for…

Virtual Algorithms Center (VIRAL)

Established: December 27, 2013

MSR has a strong group of scientists working on algorithm design, analysis, and experimental evaluation, as well as researchers in related areas (e.g., coding theory), but no formal algorithms group. The Virtual Algorithms Center (VIRAL) brings these individuals together. The goals of the center is to enhance collaboration between algorithms researchers and the rest of MSR, provide internal consulting, and give an external view of the algorithms research at MSR.

Thresholding based Efficient Outlier Robust PCA

Yeshwanth Cherapanamjeri, Prateek Jain, Praneeth Netrapalli, in COLT-2017, February 18, 2017, View abstract, Download PDF, View external link

ProtoNN: Compressed and Accurate kNN for Resource-scarce Devices

Ankit Gupta, Chirag GuptaArun Sai Suggala, Ankit Gupta, Harsha Simhadri, Bhargavi Paranjape, Ashish Kumar, Saurabh Goyal, Raghavendra Udupa, Manik Varma, Prateek Jain, in Proceedings of the 34th International Conference on Machine Learning, Sydney, Australia, PMLR 70, February 8, 2017, View abstract, Download PDF

Selective Inference for Group-Sparse Linear Models

Fan Yang, Rina Foygel Barber, Prateek Jain, John Lafferty, July 27, 2016, View abstract, Download PDF, View external link

Nearly-optimal Robust Matrix Completion

Yeshwanth Cherapanamjeri, Kartik Gupta, Prateek Jain, July 14, 2016, View abstract, Download PDF, View external link

Streaming PCA: Matching Matrix Bernstein and Near-Optimal Finite Sample Guarantees for Oja’s Algorithm

Prateek Jain, Chi Jin, Sham Kakade, Praneeth Netrapalli, Aaron Sidford, in Proceedings of The 29th Conference on Learning Theory (COLT), June 25, 2016, View abstract, Download PDF, View external link

Efficient and Consistent Robust Time Series Analysis

Kush Bhatia, Prateek Jain, Purushottam Kar, Kamalaurben Parameswaran, June 21, 2016, View abstract, Download PDF, View external link

Diverse Yet Efficient Retrieval using Hash Functions

Vidyadhar Rao, Prateek Jain, C V Jawahar, in Proceedings of ACM International Conference in Multimedia Retrieval (ICMR), June 6, 2016, View abstract, Download PDF, View external link

Structured Sparse Regression via Greedy Hard-Thresholding

Prateek Jain, Nikhil Rao, Inderjit S. Dhillon, May 27, 2016, View abstract, Download PDF, View external link

Tensor vs Matrix Methods: Robust Tensor Decomposition under Block Sparse Perturbations

Anima Anandkumar, Prateek Jain, Yang Shi, U N Niranjan, in Proceedings of the 19th International Conference on Artificial Intelligence and Statistics (AISTATS), May 10, 2016, View abstract, Download PDF, View external link

Alternating Minimization for Regression Problems with Vector-valued Outputs

Prateek Jain, Ambuj Tewari, in Proceedings of the 28th Annual Conference on Advances in Neural Information Processing Systems (NIPS), December 10, 2015, View abstract, Download PDF

Predtron: A Family of Online Algorithms for General Prediction Problems

Prateek Jain, Nagarajan Natarajan, Ambuj Tewari, in Proceedings of the 28th Annual Conference on Advances in Neural Information Processing Systems (NIPS), December 10, 2015, View abstract, Download PDF

Robust Regression via Hard Thresholding

Kush Bhatia, Prateek Jain, Purushottam Kar, in Proceedings of the 28th Annual Conference on Advances in Neural Information Processing Systems (NIPS), December 10, 2015, View abstract, Download PDF, View external link

Sparse Local Embeddings for Extreme Multi-label Classification

Kush Bhatia, Himanshu Jain, Purushottam Kar, Manik Varma, Prateek Jain, in Proceedings of the 28th Annual Conference on Advances in Neural Information Processing Systems (NIPS), December 10, 2015, View abstract, Download PDF, View external link

Efficient Matrix Sensing Using Rank-1 Gaussian Measurements

Kai Zhong, Prateek Jain, Inderjit S. Dhillon, in Proceedings of 26th International Conference on Algorithmic Learning Theory (ALT), October 14, 2015, View abstract, Download PDF

Phase Retrieval using Alternating Minimization

Praneeth Netrapalli, Prateek Jain, Sujay Sanghavi, in IEEE Transactions on Signal Processing 2015. An extended abstract appeared in 27th Annual Conference on Neural Information Processing Systems 2013., October 1, 2015, View abstract, View external link

Optimizing Non-decomposable Performance Measures: A Tale of Two Classes

, Prateek Jain, in Proceedings of the 32nd International Conference on Machine Learning (ICML), Journal of Machine Learning Research, July 1, 2015, View abstract, View external link

Surrogate Functions for Maximizing Precision at the Top

Purushottam Kar, Harikrishna Narasimhan, Prateek Jain, in Proceedings of the 32nd International Conference on Machine Learning (ICML), Journal of Machine Learning Research, July 1, 2015, View abstract, View external link

Fast Exact Matrix Completion with Finite Samples

Prateek Jain, Praneeth Netrapalli, in Proceedings of The 28th Conference on Learning Theory (COLT), June 24, 2015, View abstract, Download PDF, View external link

Tighter Low-rank Approximation via Sampling the Leveraged Element

Prateek Jain, Srinadh Bhojanapalli, Sujay Sanghavi, in Proceedings of the Twenty-Sixth Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), January 7, 2015, View abstract, Download PDF, View external link

Tighter Low-rank Approximation via Sampling the Leveraged Element

Srinadh Bhojanapalli, Prateek Jain, Sujay Sanghavi, SIAM – Society for Industrial and Applied Mathematics, January 1, 2015, View abstract

Provable Submodular Minimization Using Wolfe’s Algorithm

Deeparnab Chakrabarty, Prateek Jain, Pravesh Kothari, in NIPS'14 Proceedings of the 27th International Conference on Neural Information Processing Systems, Montreal, Canada, MIT Press Cambridge, MA, USA, December 8, 2014, View abstract, Download PDF

Non-convex Robust PCA

Praneeth Netrapalli, U N Niranjan, Sujay Sanghavi, Anima Anandkumar, Prateek Jain, Neural Information Processing Systems, December 1, 2014, View abstract, Download PDF, View external link

On Iterative Hard Thresholding Methods for High-dimensional M-Estimation

Prateek Jain, Ambuj Tewari, Purushottam Kar, in Proceedings of the 28th Annual Conference on Neural Information Processing Systems (NIPS), Neural Information Processing Systems, December 1, 2014, View abstract, View external link

Online and Stochastic Gradient Methods for Non-decomposable Loss Functions

Purushottam Kar, Harikrishna Narasimhan, Prateek Jain, in Proceedings of the 28th Annual Conference on Neural Information Processing Systems (NIPS), Neural Information Processing Systems, December 1, 2014, View abstract, View external link

Learning Mixtures of Discrete Product Distributions using Spectral Decompositions

Prateek Jain, Sewoong Oh, in Proceedings of The 27th Conference on Learning Theory, COLT 2014, Barcelona, Spain, June 13-15, 2014, July 1, 2014, View abstract, Download PDF, View external link

Learning Sparsely Used Overcomplete Dictionaries

Alekh Agarwal, Animashree Anandkumar, Prateek Jain, Praneeth Netrapalli, Rashish Tandon, in Proceedings of The 27th Conference on Learning Theory, COLT 2014, Barcelona, Spain, June 13-15, 2014, July 1, 2014, View abstract, Download PDF, View external link

Universal Matrix Completion

Srinadh Bhojanapalli, Prateek Jain, in Proceedings of the 31th International Conference on Machine Learning, ICML 2014, Beijing, China, 21-26 June 2014, July 1, 2014, View abstract, View external link

(Near) Dimension Independent Risk Bounds for Differentially Private Learning

Prateek Jain, Abhradeep Guha Thakurta, in Proceedings of the 31th International Conference on Machine Learning, ICML 2014, Beijing, China, 21-26 June 2014, June 1, 2014, View abstract, Download PDF, View external link

Large-scale Multi-label Learning with Missing Labels

Hsiang-Fu Yu, Prateek Jain, Purushottam Kar, Inderjit Dhillon, in Proceedings of the 31st International Conference on Machine Learning (ICML), Journal of Machine Learning Research, June 1, 2014, View abstract, View external link

Hashing Hyperplane Queries to Near Points with Applications to Large-Scale Active Learning

Sudheendra Vijayanarasimhan, Prateek Jain, Kristen Grauman, in IEEE Trans. Pattern Anal. Mach. Intell. (PAMI), January 1, 2014, View abstract, View external link

Memory Limited, Streaming PCA

Ioannis Mitliagkas, Constantine Caramanis, Prateek Jain, in Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013, Lake Tahoe, Nevada, United States., December 1, 2013, View abstract, View external link

Improved Multiple Sequence Alignments Using Coupled Pattern Mining

K. S. M. Tozammel Hossain, Debprakash Patnaik, Srivatsan Laxman, Prateek Jain, Chris Bailey-Kellogg, Naren Ramakrishnan, in IEEE/ACM Trans. Comput. Biology Bioinform., November 1, 2013, View abstract, View external link

Differentially Private Learning with Kernels

Prateek Jain, Abhradeep Thakurta, in Proceedings of the 30th International Conference on Machine Learning, ICML 2013, Atlanta, GA, USA, 16-21 June 2013, July 1, 2013, View abstract, Download PDF, View external link

Low-rank matrix completion using alternating minimization

Prateek Jain, Praneeth Netrapalli, Sujay Sanghavi, in Symposium on Theory of Computing, STOC'13, Palo Alto, CA, USA, June 1-4, 2013, June 1, 2013, View abstract, View external link

One-bit Compressed Sensing: Provable Support and Vector Recovery

Sivakant Gopi, Praneeth Netrapalli, Prateek Jain, Aditya Nori, in International Conference on Machine Learning (ICML), Journal of Machine Learning Research, June 1, 2013, View abstract, Download PDF

On the Generalization Ability of Online Learning Algorithms for Pairwise Loss Functions

Purushottam Kar, Bharath K. Sriperumbudur, Prateek Jain, Harish C. Karnick, in Proceedings of the 30th International Conference on Machine Learning, Journal of Machine Learning Research, January 1, 2013, View abstract, Download PDF, View external link

Multilabel Classification using Bayesian Compressed Sensing

Ashish Kapoor, Prateek Jain, Raajay Viswanathan, in Advances in Neural Information Processing Systems 25 (NIPS 2012), December 3, 2012, View abstract, Download PDF

Differentially Private Online Learning

Prateek Jain, Pravesh Kothari, Abhradeep Thakurta, in Annual Conference on Learning Theory (COLT), July 1, 2012, View abstract, Download PDF

Metric and Kernel Learning using a Linear Transformation

Prateek Jain, in Journal of Machine Learning (JMLR), January 1, 2012, View abstract

Mirror Descent Based Database Privacy

Prateek Jain, in Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques - 15th International Workshop, APPROX 2012, and 16th International Workshop, RANDOM 2012, Cambridge, MA, USA, August 15-17, 2012. Proceedings, January 1, 2012, View abstract, View external link

Supervised Learning with Similarity Functions

Purushottam Kar, Prateek Jain, in 26th Annual Conference on Neural Information Processing Systems (NIPS), Neural Information Processing Systems Foundation, January 1, 2012, View abstract, Download PDF

Similarity-based Learning via Data driven Embeddings

Purushottam Kar, Prateek Jain, in 25th Annual Conference on Neural Information Processing Systems (NIPS), December 1, 2011, View abstract, View external link

A Learning Framework for Self-Tuning Histograms

Prateek Jain, Srivatsan Laxman, Arvind Arasu, in Arxiv: 1111.7925, January 1, 2011, View abstract

Orthogonal Matching Pursuit with Replacement

Prateek Jain, in NIPS, January 1, 2011, View abstract

Far-sighted active learning on a budget for image and video recognition

Prateek Jain, in The Twenty-Third IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2010, San Francisco, CA, USA, 13-18 June 2010, January 1, 2010, View abstract, View external link

Guaranteed Rank Minimization via Singular Value Projection

Prateek Jain, in Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, Vancouver, British Columbia, Canada., January 1, 2010, View abstract, View external link

Hashing Hyperplane Queries to Near Points with Applications to Large-Scale Active Learning

Inductive Regularized Learning of Kernel Functions

Prateek Jain, Brian Kulis, Inderjit S. Dhillon, in Advances in Neural Information Processing Systems (NIPS), January 1, 2010, View abstract, Download PDF, View external link

Active Learning for Large Multi-Class Problems

Prateek Jain, Ashish Kapoor, in IEEE Conference on Computer Vision and Pattern Recognition, 2009. CVPR 2009, IEEE, June 20, 2009, View abstract, Download PDF

Fast Similarity Search for Learned Metrics

Prateek Jain, in IEEE Trans. Pattern Anal. Mach. Intell., January 1, 2009, View abstract, View external link

Geometry-aware Metric Learning

Zhengdong Lu, Prateek Jain, Inderjit S. Dhillon, in International Conference on Machine Learning (ICML), January 1, 2009, View abstract, Download PDF

Matrix Completion from Power-Law Distributed Samples

Prateek Jain, in Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, Vancouver, British Columbia, Canada., January 1, 2009, View abstract, View external link

Fast image search for learned metrics

Prateek Jain, in 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2008), 24-26 June 2008, Anchorage, Alaska, USA, January 1, 2008, View abstract, View external link

Online Metric Learning and Fast Similarity Search

Prateek Jain, in Advances in Neural Information Processing Systems 21, Proceedings of the Twenty-Second Annual Conference on Neural Information Processing Systems, Vancouver, British Columbia, Canada, December 8-11, 2008, January 1, 2008, View abstract, View external link

October 9, 2012

Speakers

Prateek Jain

Affiliation

Microsoft Research India

Projects

Non-convex Optimization for High-Dimensional Statistics
Matrix Completion and Low-rank Matrix Recovery
Compressive Sensing
Learning with Non-decomposable Loss Functions
Differential Privacy for Machine Learning
Distance Metric Learning

About

Projects

Publications

2017

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

Projects

Date

Speakers

Affiliation

Date

Speakers

Affiliation

Date

Speakers

Affiliation

Date

Speakers

Affiliation

Date

Speakers

Affiliation

Date

Speakers

Affiliation

Date

Speakers

Affiliation

Date

Speakers

Affiliation

Date

Speakers

Affiliation

Date

Speakers

Affiliation

Other

Projects

Follow Microsoft Research

Share this page