Raghu Meka

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Adam KlivansProfessor of Computer Science, University of Texas at AustinVerified email at cs.utexas.edu
Parikshit GopalanAppleVerified email at apple.com
David ZuckermanProfessor of Computer Science, University of Texas at AustinVerified email at cs.utexas.edu
Prateek JainGoogle Research IndiaVerified 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
Omer ReingoldStanford UniversityVerified email at stanford.edu
Shachar LovettAssociate Professor of Computer Science, University of California San DiegoVerified email at eng.ucsd.edu
Daniel KaneUniversity of California, San DiegoVerified email at ucsd.edu
Pravesh K. KothariCarnegie Mellon UniversityVerified email at cs.cmu.edu
Prahladh HarshaTata Institute of Fundamental Research, MumbaiVerified email at tifr.res.in
Sitan ChenUC BerkeleyVerified email at berkeley.edu
Nikhil BansalUniversity of MichiganVerified email at umich.edu
Salil VadhanVicky Joseph Professor of Computer Science and Applied Mathematics, Harvard UniversityVerified email at g.harvard.edu
Thomas WatsonAssociate Professor of Computer Science, University of MemphisVerified email at memphis.edu
Mika GöösEPFLVerified email at epfl.ch
Russell ImpagliazzoUC, San DiegoVerified email at eng.ucsd.edu
Johan HåstadProfessor i teoretisk datalogi, KTHVerified email at kth.se
Boaz BarakHarvard UniversityVerified email at boazbarak.org
David SteurerETH ZürichVerified email at inf.ethz.ch
Avishay TalUC BerkeleyVerified email at berkeley.edu

Raghu Meka

University of California, Los Angeles

Verified email at cs.ucla.edu - Homepage

Theoretical computer science


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Guaranteed rank minimization via singular value projection P Jain, R Meka, I Dhillon Advances in Neural Information Processing Systems 23, 2010	529	2010
Constructive discrepancy minimization by walking on the edges S Lovett, R Meka SIAM Journal on Computing 44 (5), 1573-1582, 2015	159	2015
Efficient algorithms for outlier-robust regression A Klivans, PK Kothari, R Meka Conference On Learning Theory, 1420-1430, 2018	136	2018
Simultaneous unsupervised learning of disparate clusterings P Jain, R Meka, IS Dhillon Statistical Analysis and Data Mining: The ASA Data Science Journal 1 (3 …, 2008	122	2008
Sum-of-squares lower bounds for planted clique R Meka, A Potechin, A Wigderson Proceedings of the forty-seventh annual ACM symposium on Theory of computing …, 2015	109	2015
Pseudorandom generators for polynomial threshold functions R Meka, D Zuckerman Proceedings of the Forty-second ACM Symposium on Theory of Computing, 427-436, 2010	105	2010
Learning graphical models using multiplicative weights A Klivans, R Meka 2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS …, 2017	99	2017
Better pseudorandom generators from milder pseudorandom restrictions P Gopalan, R Meka, O Reingold, L Trevisan, S Vadhan 2012 IEEE 53rd Annual Symposium on Foundations of Computer Science, 120-129, 2012	89	2012
Polynomial-time approximation schemes for knapsack and related counting problems using branching programs P Gopalan, A Klivans, R Meka arXiv preprint arXiv:1008.3187, 2010	85*	2010
Pseudorandomness from shrinkage R Impagliazzo, R Meka, D Zuckerman 2012 IEEE 53rd Annual Symposium on Foundations of Computer Science, 111-119, 2012	81	2012
Making the long code shorter B Barak, P Gopalan, J Håstad, R Meka, P Raghavendra, D Steurer 2012 IEEE 53rd Annual Symposium on Foundations of Computer Science, 370-379, 2012	81	2012
Guaranteed rank minimization via singular value projection R Meka, P Jain, IS Dhillon arXiv preprint arXiv:0909.5457, 2009	77	2009
Almost optimal explicit Johnson-Lindenstrauss families D Kane, R Meka, J Nelson Approximation, Randomization, and Combinatorial Optimization. Algorithms and …, 2011	74	2011
Rank minimization via online learning R Meka, P Jain, C Caramanis, IS Dhillon Proceedings of the 25th International Conference on Machine learning, 656-663, 2008	73	2008
Learning one convolutional layer with overlapping patches S Goel, A Klivans, R Meka International Conference on Machine Learning, 1783-1791, 2018	72	2018
Bounding the sensitivity of polynomial threshold functions P Harsha, A Klivans, R Meka arXiv preprint arXiv:0909.5175, 2009	70*	2009
Rectangles are nonnegative juntas M Goos, S Lovett, R Meka, T Watson, D Zuckerman SIAM Journal on Computing 45 (5), 1835-1869, 2016	66	2016
Matrix completion from power-law distributed samples R Meka, P Jain, I Dhillon Advances in neural information processing systems 22, 2009	66	2009
DNF sparsification and a faster deterministic counting algorithm P Gopalan, R Meka, O Reingold computational complexity 22 (2), 275-310, 2013	64	2013
Rectangles are nonnegative juntas M Göös, S Lovett, R Meka, T Watson, D Zuckerman Proceedings of the forty-seventh annual ACM symposium on Theory of Computing …, 2015	62	2015

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