| Low-rank matrix completion using alternating minimization P Jain, P Netrapalli, S Sanghavi Proceedings of the forty-fifth annual ACM symposium on Theory of computing …, 2013 | 729 | 2013 |
| Phase retrieval using alternating minimization P Netrapalli, P Jain, S Sanghavi Advances in Neural Information Processing Systems, 2796-2804, 2013 | 418 | 2013 |
| How to escape saddle points efficiently C Jin, R Ge, P Netrapalli, SM Kakade, MI Jordan Proceedings of the 34th International Conference on Machine Learning-Volume …, 2017 | 288 | 2017 |
| Non-convex robust PCA P Netrapalli, UN Niranjan, S Sanghavi, A Anandkumar, P Jain Advances in Neural Information Processing Systems, 1107-1115, 2014 | 213 | 2014 |
| Learning the graph of epidemic cascades P Netrapalli, S Sanghavi ACM SIGMETRICS Performance Evaluation Review 40 (1), 211-222, 2012 | 145 | 2012 |
| Learning sparsely used overcomplete dictionaries via alternating minimization A Agarwal, A Anandkumar, P Jain, P Netrapalli SIAM Journal on Optimization 26 (4), 2775-2799, 2016 | 134 | 2016 |
| Learning sparsely used overcomplete dictionaries A Agarwal, A Anandkumar, P Jain, P Netrapalli, R Tandon Conference on Learning Theory, 123-137, 2014 | 94 | 2014 |
| Accelerated gradient descent escapes saddle points faster than gradient descent C Jin, P Netrapalli, MI Jordan arXiv preprint arXiv:1711.10456, 2017 | 91 | 2017 |
| Streaming PCA: Matching matrix Bernstein and near-optimal finite sample guarantees for Oja’s algorithm P Jain, C Jin, SM Kakade, P Netrapalli, A Sidford Conference on learning theory, 1147-1164, 2016 | 87* | 2016 |
| Information-theoretic thresholds for community detection in sparse networks J Banks, C Moore, J Neeman, P Netrapalli Conference on Learning Theory, 383-416, 2016 | 85* | 2016 |
| Faster Eigenvector Computation via Shift-and-Invert Preconditioning. D Garber, E Hazan, C Jin, SM Kakade, C Musco, P Netrapalli, A Sidford ICML, 2626-2634, 2016 | 81* | 2016 |
| A clustering approach to learning sparsely used overcomplete dictionaries A Agarwal, A Anandkumar, P Netrapalli IEEE Transactions on Information Theory 63 (1), 575-592, 2016 | 75* | 2016 |
| Fast exact matrix completion with finite samples P Jain, P Netrapalli Conference on Learning Theory, 1007-1034, 2015 | 67 | 2015 |
| Parallelizing stochastic gradient descent for least squares regression: mini-batching, averaging, and model misspecification P Jain, P Netrapalli, SM Kakade, R Kidambi, A Sidford The Journal of Machine Learning Research 18 (1), 8258-8299, 2017 | 61* | 2017 |
| Provable efficient online matrix completion via non-convex stochastic gradient descent C Jin, SM Kakade, P Netrapalli Advances in Neural Information Processing Systems, 4520-4528, 2016 | 61 | 2016 |
| One-bit compressed sensing: Provable support and vector recovery S Gopi, P Netrapalli, P Jain, A Nori International Conference on Machine Learning, 154-162, 2013 | 58 | 2013 |
| Accelerating stochastic gradient descent for least squares regression P Jain, SM Kakade, R Kidambi, P Netrapalli, A Sidford arXiv preprint arXiv:1704.08227, 2017 | 55* | 2017 |
| Greedy learning of Markov network structure P Netrapalli, S Banerjee, S Sanghavi, S Shakkottai 2010 48th Annual Allerton Conference on Communication, Control, and …, 2010 | 50 | 2010 |
| Efficient algorithms for large-scale generalized eigenvector computation and canonical correlation analysis R Ge, C Jin, P Netrapalli, A Sidford International Conference on Machine Learning, 2741-2750, 2016 | 37 | 2016 |
| Convergence rates of active learning for maximum likelihood estimation SS K Chaudhuri, SM Kakade, P Netrapalli Proceedings of the 28th International Conference on Neural Information …, 2015 | 34* | 2015 |
Prateek JainMicrosoft Research IndiaVerified email at microsoft.com
