Sujay Sanghavi

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Constantine CaramanisProfessor of Electrical and Computer Engineering, UT AustinVerified email at utexas.edu
Alan S. WillskyProfessor of EECS, MITVerified email at mit.edu
Praneeth NetrapalliGoogle ResearchVerified email at google.com
Ali JalaliUniversity of Texas at AustinVerified email at mail.utexas.edu
Inderjit S. DhillonDistinguished Scientist at Google & Professor of Computer Science at UT Austin, Ex-VP at AmazonVerified email at cs.utexas.edu
Huan XuAlibaba IncVerified email at alibaba-inc.com
Anastasios KyrillidisAssociate Professor, Computer Science Department, Ken Kennedy Institute Fellow, Rice UniversityVerified email at rice.edu
Yudong ChenAssociate Professor, University of Wisconsin-MadisonVerified email at wisc.edu
Prateek JainGoogle Research IndiaVerified email at google.com
Dohyung ParkThe University of Texas at AustinVerified email at utexas.edu
Srinadh BhojanapalliResearch Scientist, Google ResearchVerified email at google.com
Pablo A. ParriloProfessor of Electrical Engineering and Computer Science, Massachusetts Institute of TechnologyVerified email at mit.edu
Dmitry MalioutovResearch Staff Member, T.J. Watson IBM Research centerVerified email at us.ibm.com
Yanyao ShenUniversity of Texas at AustinVerified email at utexas.edu
Bruce HajekProfessor of Electrical and Computer Engineering, University of IllinoisVerified email at illinois.edu
Pradeep RavikumarProfessor, School of Computer Science, Carnegie Mellon UniversityVerified email at cs.cmu.edu
Alexandros G DimakisProfessor, ECE University of Texas at AustinVerified email at austin.utexas.edu
Rachel WardVerified email at math.utexas.edu
R. SrikantUniversity of Illinois at Urbana-ChampaignVerified email at illinois.edu
Devavrat ShahMassachusetts Institute of TechnologyVerified email at mit.edu

Sujay Sanghavi

Associate Professor, Electrical and Computer Engineering, University of Texas, Austin

Verified email at mail.utexas.edu - Homepage

Machine Learning Optimization and Algorithms Networks


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Rank-sparsity incoherence for matrix decomposition V Chandrasekaran, S Sanghavi, PA Parrilo, AS Willsky SIAM Journal on Optimization 21 (2), 572-596, 2011	1266	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	1222	2013
Robust PCA via outlier pursuit H Xu, C Caramanis, S Sanghavi Advances in neural information processing systems 23, 2010	890	2010
Phase retrieval using alternating minimization P Netrapalli, P Jain, S Sanghavi Advances in Neural Information Processing Systems 26, 2013	722	2013
A dirty model for multi-task learning A Jalali, S Sanghavi, C Ruan, P Ravikumar Advances in neural information processing systems 23, 2010	488	2010
Non-convex robust PCA P Netrapalli, N UN, S Sanghavi, A Anandkumar, P Jain Advances in neural information processing systems 27, 2014	359	2014
Learning with bad training data via iterative trimmed loss minimization Y Shen, S Sanghavi International conference on machine learning, 5739-5748, 2019	287	2019
Convergence rates of sub-sampled Newton methods MA Erdogdu, A Montanari arXiv preprint arXiv:1508.02810, 2015	259*	2015
Learning the graph of epidemic cascades P Netrapalli, S Sanghavi ACM SIGMETRICS Performance Evaluation Review 40 (1), 211-222, 2012	230	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	223	2013
Sparse and low-rank matrix decompositions V Chandrasekaran, S Sanghavi, PA Parrilo, AS Willsky IFAC Proceedings Volumes 42 (10), 1493-1498, 2009	204	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	196	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	188	2017
Dropping convexity for faster semi-definite optimization S Bhojanapalli, A Kyrillidis, S Sanghavi Conference on Learning Theory, 530-582, 2016	183	2016
Gossiping with multiple messages S Sanghavi, B Hajek, L Massoulié IEEE Transactions on Information Theory 53 (12), 4640-4654, 2007	183	2007
Sequential compressed sensing DM Malioutov, SR Sanghavi, AS Willsky Selected Topics in Signal Processing, IEEE Journal of 4 (2), 435-444, 2010	171	2010
Alternating minimization for mixed linear regression X Yi, C Caramanis, S Sanghavi International Conference on Machine Learning, 613-621, 2014	160	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
Robust matrix completion and corrupted columns Y Chen, H Xu, C Caramanis, S Sanghavi Proceedings of the 28th International Conference on Machine Learning (ICML …, 2011	147	2011

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