Elad Hazan

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Satyen KaleResearch Scientist, Google ResearchDirección de correo verificada de google.com
Naman AgarwalSenior Research Scientist, Google AI PrincetonDirección de correo verificada de google.com
Sanjeev AroraProfessor of Computer Science, Princeton UniversityDirección de correo verificada de cs.princeton.edu
Xinyi ChenPrinceton University, Google DeepMindDirección de correo verificada de princeton.edu
Cyril ZhangMicrosoft Research NYCDirección de correo verificada de microsoft.com
Brian BullinsAssistant Professor, Purdue UniversityDirección de correo verificada de purdue.edu
Tomer KorenAssociate Professor at Tel Aviv UniversityDirección de correo verificada de tauex.tau.ac.il
Dan GarberAssociate Professor at Technion - Israel Institute of TechnologyDirección de correo verificada de technion.ac.il
John DuchiAssociate Professor of Statistics and Electrical Engineering, Stanford UniversityDirección de correo verificada de stanford.edu
Zeyuan Allen-ZhuMeta AI / FAIR LabsDirección de correo verificada de csail.mit.edu
Jacob AbernethyAssistant Professor, University of MichiganDirección de correo verificada de umich.edu
Sham M KakadeHarvard UniversityDirección de correo verificada de seas.harvard.edu
Alexander RakhlinProfessor, MITDirección de correo verificada de mit.edu
Udaya GhaiAmazon, NYCDirección de correo verificada de amazon.com
Tengyu MAStanford UniversityDirección de correo verificada de stanford.edu
Karan SinghCarnegie Mellon UniversityDirección de correo verificada de cmu.edu
Oren AnavaTechnionDirección de correo verificada de tx.technion.ac.il
Kfir Yehuda LevyAssistant Professor at Technion - Israel Institute of TechnologyDirección de correo verificada de technion.ac.il
Shie MannorProfessor of Electrical Engineering @ Technion & Researcher @ NvidiaDirección de correo verificada de technion.ac.il
Paula GraduPhD student, UC BerkeleyDirección de correo verificada de berkeley.edu

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Elad Hazan

Professor at Princeton University and Director Google AI Princeton

Dirección de correo verificada de princeton.edu - Página principal

Machine Learning Mathematical Optimization


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
Adaptive subgradient methods for online learning and stochastic optimization. J Duchi, E Hazan, Y Singer Journal of machine learning research 12 (7), 2011	14082	2011
Introduction to online convex optimization E Hazan Foundations and Trends® in Optimization 2 (3-4), 157-325, 2016	2045	2016
Logarithmic regret algorithms for online convex optimization E Hazan, A Agarwal, S Kale Machine Learning 69 (2), 169-192, 2007	1332	2007
The multiplicative weights update method: a meta-algorithm and applications S Arora, E Hazan, S Kale Theory of computing 8 (1), 121-164, 2012	1250	2012
On the optimization of deep networks: Implicit acceleration by overparameterization S Arora, N Cohen, E Hazan International conference on machine learning, 244-253, 2018	540	2018
Variance reduction for faster non-convex optimization Z Allen-Zhu, E Hazan International conference on machine learning, 699-707, 2016	438	2016
Competing in the Dark: An Efficient Algorithm for Bandit Linear Optimization. JD Abernethy, E Hazan, A Rakhlin COLT, 263-274, 2008	410	2008
Second-order stochastic optimization for machine learning in linear time N Agarwal, B Bullins, E Hazan Journal of Machine Learning Research 18 (116), 1-40, 2017	335*	2017
Beyond the regret minimization barrier: optimal algorithms for stochastic strongly-convex optimization E Hazan, S Kale The Journal of Machine Learning Research 15 (1), 2489-2512, 2014	315	2014
Provably efficient maximum entropy exploration E Hazan, S Kakade, K Singh, A Van Soest International Conference on Machine Learning, 2681-2691, 2019	308	2019
Algorithms for portfolio management based on the newton method A Agarwal, E Hazan, S Kale, RE Schapire Proceedings of the 23rd international conference on Machine learning, 9-16, 2006	283	2006
Finding approximate local minima faster than gradient descent N Agarwal, Z Allen-Zhu, B Bullins, E Hazan, T Ma Proceedings of the 49th Annual ACM SIGACT Symposium on Theory of Computing …, 2017	270	2017
Adaptive online gradient descent E Hazan, A Rakhlin, P Bartlett Advances in neural information processing systems 20, 2007	269	2007
Projection-free online learning E Hazan, S Kale arXiv preprint arXiv:1206.4657, 2012	266	2012
On the complexity of approximating k-set packing E Hazan, S Safra, O Schwartz computational complexity 15 (1), 20-39, 2006	258*	2006
Online control with adversarial disturbances N Agarwal, B Bullins, E Hazan, S Kakade, K Singh International Conference on Machine Learning, 111-119, 2019	247	2019
Efficient learning algorithms for changing environments E Hazan, C Seshadhri Proceedings of the 26th annual international conference on machine learning …, 2009	231	2009
Faster rates for the Frank-Wolfe method over strongly-convex sets D Garber, E Hazan International Conference on Machine Learning, 541-549, 2015	217	2015
Sparse approximate solutions to semidefinite programs E Hazan Latin American symposium on theoretical informatics, 306-316, 2008	208	2008
Variance-reduced and projection-free stochastic optimization E Hazan, H Luo International Conference on Machine Learning, 1263-1271, 2016	193	2016

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