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Inderjit S. DhillonDistinguished Scientist at Google & Professor of Computer Science at UT Austin, Ex-VP at AmazonPatvirtintas el. paštas cs.utexas.edu
Stefanie JegelkaTUM and MITPatvirtintas el. paštas mit.edu
Sashank J. ReddiResearch Scientist, Google ResearchPatvirtintas el. paštas cs.cmu.edu
Jingzhao ZhangIIIS, Tsinghua UniversityPatvirtintas el. paštas mit.edu
Ali JadbabaieJR East Professor of Engineering, MITPatvirtintas el. paštas mit.edu
Alex SmolaBoson AIPatvirtintas el. paštas smola.org
Anoop CherianMitsubishi Electric Research Labs (MERL), Australian National UniversityPatvirtintas el. paštas merl.com
Arindam BanerjeeFounder Professor, Dept of Computer Science, University of Illinois Urbana-ChampaignPatvirtintas el. paštas illinois.edu
Chulhee YunAssistant Professor, KAIST Kim Jaechul Graduate School of AIPatvirtintas el. paštas kaist.ac.kr
Reshad HosseiniAssistant Professor, Machine Learning and Robotics Group, University of TehranPatvirtintas el. paštas tuebingen.mpg.de
Bernhard SchölkopfDirector, Max Planck Institute for Intelligent Systems & ELLIS Institute Tübingen; Professor at ETHPatvirtintas el. paštas tuebingen.mpg.de
Brian KulisAssociate Professor at Boston University & Amazon ScholarPatvirtintas el. paštas bu.edu
Barnabas PoczosAssociate professor, Carnegie Mellon UniversityPatvirtintas el. paštas cs.cmu.edu
Sebastian NowozinGoogle DeepMindPatvirtintas el. paštas deepmind.com
Joshua RobinsonStanfordPatvirtintas el. paštas mit.edu
Stephen WrightDepartment of Computer Sciences and Wisconsin Institute for Discovery, University of WisconsinPatvirtintas el. paštas cs.wisc.edu
Ahmed HefnyApplied Research Scientist, CruisePatvirtintas el. paštas getcruise.com
Kwangjun AhnMicrosoft ResearchPatvirtintas el. paštas microsoft.com
Chengtao LiGalixirPatvirtintas el. paštas galixir.com
Michael HirschMax Planck Institute for Intelligent Systems TübingenPatvirtintas el. paštas tuebingen.mpg.de

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Suvrit Sra

TUM and MIT

Patvirtintas el. paštas mit.edu - Pagrindinis puslapis

Nonconvex Optimization Deep Learning Theory Matrix Analysis Geometric Optimization


Pavadinimas Rūšiuoti pagal šaltinius Rūšiuoti pagal metus Rūšiuoti pagal pavadinimą	Cituota Cituota	Metai
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	2683	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	1214	2005
Optimization for machine learning S Sra, S Nowozin, SJ Wright Mit Press, 2011	1026	2011
Contrastive learning with hard negative samples J Robinson, CY Chuang, S Sra, S Jegelka ICLR 2021, 2021	859	2021
Stochastic Variance Reduction for Nonconvex Optimization SJ Reddi, A Hefny, S Sra, B Póczós, A Smola International Conference on Machine Learning (ICML), 2016	683	2016
Generalized nonnegative matrix approximations with Bregman divergences S Sra, I Dhillon Advances in neural information processing systems 18, 2005	662	2005
Why gradient clipping accelerates training: A theoretical justification for adaptivity J Zhang, T He, S Sra, A Jadbabaie arXiv:1905.11881 (ICLR 2020), 2019	498	2019
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	441	2004
Why are adaptive methods good for attention models? J Zhang, SP Karimireddy, A Veit, S Kim, S Reddi, S Kumar, S Sra Advances in Neural Information Processing Systems 33, 15383-15393, 2020	334*	2020
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	319	2010
First-order methods for geodesically convex optimization H Zhang, S Sra Conference on Learning Theory (COLT), 2016	316	2016
Riemannian SVRG: Fast stochastic optimization on Riemannian manifolds H Zhang, S J Reddi, S Sra Advances in Neural Information Processing Systems 29, 2016	286	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	248	2016
Randomized nonlinear component analysis D Lopez-Paz, S Sra, A Smola, Z Ghahramani, B Schölkopf International conference on machine learning, 1359-1367, 2014	233	2014
Geometric Mean Metric Learning PH Zadeh, R Hosseini, S Sra International Conference on Machine Learning (ICML), 2016	219	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	215	2016
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	214	2015
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	207	2012
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	201	2012
Positive definite matrices and the S-divergence S Sra Proceedings of the American Mathematical Society 144 (7), 2787-2797, 2016	191	2016

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