Elad Hazan
Elad Hazan
Professor at Princeton University and Director Google AI Princeton
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Adaptive subgradient methods for online learning and stochastic optimization.
J Duchi, E Hazan, Y Singer
Journal of machine learning research 12 (7), 2011
Introduction to online convex optimization
E Hazan
Foundations and Trends® in Optimization 2 (3-4), 157-325, 2016
Logarithmic regret algorithms for online convex optimization
E Hazan, A Agarwal, S Kale
Machine Learning 69 (2), 169-192, 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
On the optimization of deep networks: Implicit acceleration by overparameterization
S Arora, N Cohen, E Hazan
International conference on machine learning, 244-253, 2018
Variance reduction for faster non-convex optimization
Z Allen-Zhu, E Hazan
International conference on machine learning, 699-707, 2016
Competing in the Dark: An Efficient Algorithm for Bandit Linear Optimization.
JD Abernethy, E Hazan, A Rakhlin
COLT, 263-274, 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
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
Provably efficient maximum entropy exploration
E Hazan, S Kakade, K Singh, A Van Soest
International Conference on Machine Learning, 2681-2691, 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
Adaptive online gradient descent
E Hazan, A Rakhlin, P Bartlett
Advances in neural information processing systems 20, 2007
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
Projection-free online learning
E Hazan, S Kale
arXiv preprint arXiv:1206.4657, 2012
On the complexity of approximating k-set packing
E Hazan, S Safra, O Schwartz
computational complexity 15 (1), 20-39, 2006
Online control with adversarial disturbances
N Agarwal, B Bullins, E Hazan, S Kakade, K Singh
International Conference on Machine Learning, 111-119, 2019
Efficient learning algorithms for changing environments
E Hazan, C Seshadhri
Proceedings of the 26th annual international conference on machine learning …, 2009
Faster rates for the Frank-Wolfe method over strongly-convex sets
D Garber, E Hazan
International Conference on Machine Learning, 541-549, 2015
Sparse approximate solutions to semidefinite programs
E Hazan
Latin American symposium on theoretical informatics, 306-316, 2008
Variance-reduced and projection-free stochastic optimization
E Hazan, H Luo
International Conference on Machine Learning, 1263-1271, 2016
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