Suvrit Sra

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Inderjit S. DhillonDistinguished Scientist at Google & Professor of Computer Science at UT Austin, Ex-VP at AmazonVerified email at cs.utexas.edu
Stefanie JegelkaMITVerified email at mit.edu
Sashank J. ReddiResearch Scientist, Google ResearchVerified email at cs.cmu.edu
Ali JadbabaieJR East Professor of Engineering, MITVerified email at mit.edu
Jingzhao ZhangIIIS, Tsinghua UniversityVerified email at mit.edu
Arindam BanerjeeFounder Professor, Dept of Computer Science, University of Illinois Urbana-ChampaignVerified email at illinois.edu
Alex SmolaBoson AIVerified email at smola.org
Anoop CherianMitsubishi Electric Research Labs (MERL), Australian National UniversityVerified email at merl.com
Chulhee YunAssistant Professor, KAIST Kim Jaechul Graduate School of AIVerified email at kaist.ac.kr
Reshad HosseiniAssistant Professor, Machine Learning and Robotics Group, University of TehranVerified email at tuebingen.mpg.de
Bernhard SchölkopfDirector, Max Planck Institute for Intelligent Systems; Professor at ETH ZürichVerified email at tuebingen.mpg.de
Brian KulisAssociate Professor at Boston University & Amazon ScholarVerified email at bu.edu
Barnabas PoczosAssociate professor, Carnegie Mellon UniversityVerified email at cs.cmu.edu
Sebastian NowozinDeepMindVerified email at deepmind.com
Joshua RobinsonMITVerified email at mit.edu
Michael HirschMax Planck Institute for Intelligent Systems TübingenVerified email at tuebingen.mpg.de
Ahmed HefnyApplied Research Scientist, CruiseVerified email at getcruise.com
Stephen WrightDepartment of Computer Sciences and Wisconsin Institute for Discovery, University of WisconsinVerified email at cs.wisc.edu
Stefan HarmelingProfessor at Technische Universität DortmundVerified email at tu-dortmund.de
Joydeep Ghosh(Chaired) Professor, ECE Dept., Univ. Texas at Austin; Faculty Dell Med, UT-Comp. Sc., McCombsVerified email at utexas.edu

Suvrit Sra

MIT

Verified email at mit.edu - Homepage

Nonconvex Optimization Machine Learning Matrix Analysis Convex Optimization Geometric Optimization


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Information-theoretic metric learning JV Davis, B Kulis, P Jain, S Sra, IS Dhillon Proceedings of the 24th international conference on Machine learning, 209-216, 2007	2587	2007
Clustering on the Unit Hypersphere using von Mises-Fisher Distributions. A Banerjee, IS Dhillon, J Ghosh, S Sra Journal of Machine Learning Research 6 (9), 2005	1069	2005
Optimization for machine learning S Sra, S Nowozin, SJ Wright Mit Press, 2012	880	2012
Generalized nonnegative matrix approximations with Bregman divergences S Sra, I Dhillon Advances in neural information processing systems 18, 2005	606	2005
Stochastic Variance Reduction for Nonconvex Optimization SJ Reddi, A Hefny, S Sra, B Póczós, A Smola International Conference on Machine Learning (ICML), 2016	577	2016
Minimum sum-squared residue co-clustering of gene expression data H Cho, IS Dhillon, Y Guan, S Sra Proceedings of the 2004 SIAM international conference on data mining, 114-125, 2004	428	2004
Contrastive learning with hard negative samples J Robinson, CY Chuang, S Sra, S Jegelka ICLR 2021, 2021	367	2021
Efficient filter flow for space-variant multiframe blind deconvolution M Hirsch, S Sra, B Schölkopf, S Harmeling 2010 IEEE Computer Society Conference on Computer Vision and Pattern …, 2010	279	2010
Why gradient clipping accelerates training: A theoretical justification for adaptivity J Zhang, T He, S Sra, A Jadbabaie arXiv:1905.11881 (ICLR 2020), 2019	266	2019
Riemannian SVRG: Fast stochastic optimization on Riemannian manifolds H Zhang, S J Reddi, S Sra Advances in Neural Information Processing Systems 29, 2016	234	2016
First-order methods for geodesically convex optimization H Zhang, S Sra Conference on Learning Theory (COLT), 2016	224	2016
Proximal stochastic methods for nonsmooth nonconvex finite-sum optimization SJ Reddi, S Sra, B Poczos, A Smola Advances in Neural Information Processing Systems, 2016	217	2016
Randomized nonlinear component analysis D Lopez-Paz, S Sra, A Smola, Z Ghahramani, B Schölkopf International conference on machine learning, 1359-1367, 2014	208	2014
On variance reduction in stochastic gradient descent and its asynchronous variants SJ Reddi, A Hefny, S Sra, B Poczos, AJ Smola Advances in neural information processing systems, 2647-2655, 2015	199	2015
Geometric Mean Metric Learning PH Zadeh, R Hosseini, S Sra International Conference on Machine Learning (ICML), 2016	181	2016
Jensen-bregman logdet divergence with application to efficient similarity search for covariance matrices A Cherian, S Sra, A Banerjee, N Papanikolopoulos IEEE transactions on pattern analysis and machine intelligence 35 (9), 2161-2174, 2012	181	2012
A short note on parameter approximation for von Mises-Fisher distributions: and a fast implementation of I _s(x) S Sra Computational Statistics 27, 177-190, 2012	176	2012
Positive definite matrices and the S-divergence S Sra Proceedings of the American Mathematical Society 144 (7), 2787-2797, 2016	171	2016
Entropic metric alignment for correspondence problems J Solomon, G Peyré, VG Kim, S Sra ACM Transactions on Graphics (ToG) 35 (4), 1-13, 2016	158	2016
Fast Newton-type methods for the least squares nonnegative matrix approximation problem D Kim, S Sra, I Dhillon SIAM Data Mining, 2007	157	2007

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