Rank-sparsity incoherence for matrix decomposition V Chandrasekaran, S Sanghavi, PA Parrilo, AS Willsky SIAM Journal on Optimization 21 (2), 572-596, 2011 | 1250 | 2011 |
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 | 1202 | 2013 |
Robust PCA via outlier pursuit H Xu, C Caramanis, S Sanghavi Advances in neural information processing systems 23, 2010 | 882 | 2010 |
Phase retrieval using alternating minimization P Netrapalli, P Jain, S Sanghavi Advances in Neural Information Processing Systems 26, 2013 | 706 | 2013 |
A dirty model for multi-task learning A Jalali, S Sanghavi, C Ruan, P Ravikumar Advances in neural information processing systems 23, 2010 | 482 | 2010 |
Non-convex robust PCA P Netrapalli, N UN, S Sanghavi, A Anandkumar, P Jain Advances in neural information processing systems 27, 2014 | 353 | 2014 |
Learning with bad training data via iterative trimmed loss minimization Y Shen, S Sanghavi International conference on machine learning, 5739-5748, 2019 | 272 | 2019 |
Convergence rates of sub-sampled Newton methods MA Erdogdu, A Montanari arXiv preprint arXiv:1508.02810, 2015 | 253* | 2015 |
Learning the graph of epidemic cascades P Netrapalli, S Sanghavi ACM SIGMETRICS Performance Evaluation Review 40 (1), 211-222, 2012 | 229 | 2012 |
Low-rank matrix recovery from errors and erasures Y Chen, A Jalali, S Sanghavi, C Caramanis IEEE Transactions on Information Theory 59 (7), 4324-4337, 2013 | 221 | 2013 |
Sparse and low-rank matrix decompositions V Chandrasekaran, S Sanghavi, PA Parrilo, AS Willsky IFAC Proceedings Volumes 42 (10), 1493-1498, 2009 | 201 | 2009 |
Distributed link scheduling with constant overhead S Sanghavi, L Bui, R Srikant Proceedings of the 2007 ACM SIGMETRICS international conference on …, 2007 | 200 | 2007 |
Clustering sparse graphs Y Chen, S Sanghavi, H Xu Advances in neural information processing systems 25, 2012 | 192 | 2012 |
Non-square matrix sensing without spurious local minima via the Burer-Monteiro approach D Park, A Kyrillidis, C Carmanis, S Sanghavi Artificial Intelligence and Statistics, 65-74, 2017 | 183 | 2017 |
Dropping convexity for faster semi-definite optimization S Bhojanapalli, A Kyrillidis, S Sanghavi Conference on Learning Theory, 530-582, 2016 | 182 | 2016 |
Gossiping with multiple messages S Sanghavi, B Hajek, L Massoulié IEEE Transactions on Information Theory 53 (12), 4640-4654, 2007 | 178 | 2007 |
Sequential compressed sensing DM Malioutov, SR Sanghavi, AS Willsky Selected Topics in Signal Processing, IEEE Journal of 4 (2), 435-444, 2010 | 170 | 2010 |
Alternating minimization for mixed linear regression X Yi, C Caramanis, S Sanghavi International Conference on Machine Learning, 613-621, 2014 | 157 | 2014 |
Message passing for maximum weight independent set S Sanghavi, D Shah, AS Willsky IEEE Transactions on Information Theory 55 (11), 4822-4834, 2009 | 148 | 2009 |
Clustering partially observed graphs via convex optimization Y Chen, A Jalali, S Sanghavi, H Xu The Journal of Machine Learning Research 15 (1), 2213-2238, 2014 | 145 | 2014 |