Elad Hazan
Elad Hazan
Professor at Princeton University and Director Google AI Princeton
Verified email at cs.princeton.edu - Homepage
Cited by
Cited by
Adaptive subgradient methods for online learning and stochastic optimization.
J Duchi, E Hazan, Y Singer
Journal of machine learning research 12 (7), 2011
Logarithmic regret algorithms for online convex optimization
E Hazan, A Agarwal, S Kale
Machine Learning 69 (2-3), 169-192, 2007
Introduction to online convex optimization
E Hazan
arXiv preprint arXiv:1909.05207, 2019
The multiplicative weights update method: a meta-algorithm and applications
S Arora, E Hazan, S Kale
Theory of Computing 8 (1), 121-164, 2012
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
On the complexity of approximating k-set packing
E Hazan, S Safra, O Schwartz
computational complexity 15 (1), 20-39, 2006
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
Adaptive online gradient descent
E Hazan, A Rakhlin, PL Bartlett
Advances in Neural Information Processing Systems, 65-72, 2008
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
Sparse approximate solutions to semidefinite programs
E Hazan
Latin American symposium on theoretical informatics, 306-316, 2008
Projection-free online learning
E Hazan, S Kale
arXiv preprint arXiv:1206.4657, 2012
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
On the optimization of deep networks: Implicit acceleration by overparameterization
S Arora, N Cohen, E Hazan
arXiv preprint arXiv:1802.06509, 2018
Fast algorithms for approximate semidefinite programming using the multiplicative weights update method
S Arora, E Hazan, S Kale
46th Annual IEEE Symposium on Foundations of Computer Science (FOCS'05), 339-348, 2005
Beyond the regret minimization barrier: an optimal algorithm for stochastic strongly-convex optimization
E Hazan, S Kale
Proceedings of the 24th Annual Conference on Learning Theory, 421-436, 2011
Second-order stochastic optimization for machine learning in linear time
N Agarwal, B Bullins, E Hazan
The Journal of Machine Learning Research 18 (1), 4148-4187, 2017
Efficient learning algorithms for changing environments
E Hazan, C Seshadhri
Proceedings of the 26th annual international conference on machine learning …, 2009
Extracting certainty from uncertainty: Regret bounded by variation in costs
E Hazan, S Kale
Machine learning 80 (2-3), 165-188, 2010
Faster rates for the frank-wolfe method over strongly-convex sets
D Garber, E Hazan
32nd International Conference on Machine Learning, ICML 2015, 2015
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