Raghu Meka

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Adam KlivansProfessor of Computer Science, University of Texas at AustinVerified email at cs.utexas.edu
Parikshit GopalanVMwareVerified email at vmware.com
David ZuckermanProfessor of Computer Science, University of Texas at AustinVerified email at cs.utexas.edu
Prateek JainMicrosoft Research IndiaVerified email at microsoft.com
Inderjit S. DhillonVice President/Distinguished Scientist at Amazon, and Professor, Computer Science, UT AustinVerified email at cs.utexas.edu
Omer ReingoldStanford UniversityVerified email at stanford.edu
Daniel KaneUniversity of California, San DiegoVerified email at ucsd.edu
Shachar LovettAssociate Professor of Computer Science, University of California San DiegoVerified email at eng.ucsd.edu
Prahladh HarshaTata Institute of Fundamental Research, MumbaiVerified email at tifr.res.in
Pravesh K. KothariCarnegie Mellon UniversityVerified email at cs.cmu.edu
Ashutosh KumarUCLAVerified email at cs.ucla.edu
Russell ImpagliazzoUC, San DiegoVerified email at eng.ucsd.edu
Salil VadhanVicky Joseph Professor of Computer Science and Applied Mathematics, Harvard UniversityVerified email at g.harvard.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
Thomas WatsonAssistant Professor of Computer Science, University of MemphisVerified email at memphis.edu
Mika GöösEPFLVerified email at epfl.ch
Aaron PotechinUniversity of ChicagoVerified email at uchicago.edu
Luca TrevisanBocconi UniversityVerified email at unibocconi.it

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 R Meka, P Jain, IS Dhillon arXiv preprint arXiv:0909.5457, 2009	526	2009
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	113	2008
Constructive discrepancy minimization by walking on the edges S Lovett, R Meka SIAM Journal on Computing 44 (5), 1573-1582, 2015	110	2015
Rectangles are nonnegative juntas M Goos, S Lovett, R Meka, T Watson, D Zuckerman SIAM Journal on Computing 45 (5), 1835-1869, 2016	100	2016
Pseudorandom generators for polynomial threshold functions R Meka, D Zuckerman SIAM Journal on Computing 42 (3), 1275-1301, 2013	93	2013
Efficient algorithms for outlier-robust regression A Klivans, PK Kothari, R Meka Conference On Learning Theory, 1420-1430, 2018	85	2018
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	79	2015
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	77	2012
Pseudorandomness from shrinkage R Impagliazzo, R Meka, D Zuckerman 2012 IEEE 53rd Annual Symposium on Foundations of Computer Science, 111-119, 2012	75	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	73	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	70*	2010
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	67	2008
Bounding the sensitivity of polynomial threshold functions P Harsha, A Klivans, R Meka arXiv preprint arXiv:0909.5175, 2009	64*	2009
Matrix completion from power-law distributed samples R Meka, P Jain, I Dhillon Advances in neural information processing systems 22, 1258-1266, 2009	62	2009
Learning graphical models using multiplicative weights A Klivans, R Meka 2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS …, 2017	61	2017
Almost optimal explicit Johnson-Lindenstrauss families D Kane, R Meka, J Nelson Approximation, Randomization, and Combinatorial Optimization. Algorithms and …, 2011	61	2011
Computational limits for matrix completion M Hardt, R Meka, P Raghavendra, B Weitz Conference on Learning Theory, 703-725, 2014	51	2014
DNF sparsification and a faster deterministic counting algorithm P Gopalan, R Meka, O Reingold Computational Complexity 22 (2), 275-310, 2013	50	2013
Learning one convolutional layer with overlapping patches S Goel, A Klivans, R Meka International Conference on Machine Learning, 1783-1791, 2018	48	2018
Approximating rectangles by juntas and weakly-exponential lower bounds for LP relaxations of CSPs PK Kothari, R Meka, P Raghavendra Proceedings of the 49th Annual ACM SIGACT Symposium on Theory of Computing …, 2017	47	2017

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