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
Inderjit S. DhillonDistinguished Scientist at Google & Professor of Computer Science at UT Austin, Ex-VP at AmazonVerified email at cs.utexas.edu
Ali JalaliUniversity of Texas at AustinVerified email at mail.utexas.edu
Huan XuAlibaba IncVerified email at alibaba-inc.com
Anastasios KyrillidisNoah Harding CS Associate Professor, Ken Kennedy Institute Fellow, Dean 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
Yanyao ShenUniversity of Texas at AustinVerified email at utexas.edu
Dmitry MalioutovResearch Staff Member, T.J. Watson IBM Research centerVerified email at us.ibm.com
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 WardUT Austin / Microsoft ResearchVerified 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	1290	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	1258	2013
Robust PCA via outlier pursuit H Xu, C Caramanis, S Sanghavi Advances in neural information processing systems 23, 2010	903	2010
Phase retrieval using alternating minimization P Netrapalli, P Jain, S Sanghavi Advances in Neural Information Processing Systems 26, 2013	748	2013
A dirty model for multi-task learning A Jalali, S Sanghavi, C Ruan, P Ravikumar Advances in neural information processing systems 23, 2010	491	2010
Non-convex robust PCA P Netrapalli, N UN, S Sanghavi, A Anandkumar, P Jain Advances in neural information processing systems 27, 2014	372	2014
Learning with bad training data via iterative trimmed loss minimization Y Shen, S Sanghavi International conference on machine learning, 5739-5748, 2019	309	2019
Convergence rates of sub-sampled Newton methods MA Erdogdu, A Montanari arXiv preprint arXiv:1508.02810, 2015	270*	2015
Learning the graph of epidemic cascades P Netrapalli, S Sanghavi ACM SIGMETRICS Performance Evaluation Review 40 (1), 211-222, 2012	234	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	229	2013
Sparse and low-rank matrix decompositions V Chandrasekaran, S Sanghavi, PA Parrilo, AS Willsky IFAC Proceedings Volumes 42 (10), 1493-1498, 2009	208	2009
Clustering sparse graphs Y Chen, S Sanghavi, H Xu Advances in neural information processing systems 25, 2012	203	2012
Distributed link scheduling with constant overhead S Sanghavi, L Bui, R Srikant Proceedings of the 2007 ACM SIGMETRICS international conference on …, 2007	200	2007
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	197	2017
Dropping convexity for faster semi-definite optimization S Bhojanapalli, A Kyrillidis, S Sanghavi Conference on Learning Theory, 530-582, 2016	189	2016
Gossiping with multiple messages S Sanghavi, B Hajek, L Massoulié IEEE Transactions on Information Theory 53 (12), 4640-4654, 2007	185	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	166	2014
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	150	2014
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	149	2011

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