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Ohad Shamir
Ohad Shamir
Verified email at weizmann.ac.il - Homepage
Title
Cited by
Cited by
Year
The power of depth for feedforward neural networks
R Eldan, O Shamir
Conference on learning theory, 907-940, 2016
7332016
Learnability, stability and uniform convergence
S Shalev-Shwartz, O Shamir, N Srebro, K Sridharan
The Journal of Machine Learning Research 9999, 2635-2670, 2010
675*2010
Optimal Distributed Online Prediction Using Mini-Batches.
O Dekel, R Gilad-Bachrach, O Shamir, L Xiao
Journal of Machine Learning Research 13 (1), 2012
6462012
Making gradient descent optimal for strongly convex stochastic optimization
A Rakhlin, O Shamir, K Sridharan
arXiv preprint arXiv:1109.5647, 2011
6172011
Stochastic gradient descent for non-smooth optimization: Convergence results and optimal averaging schemes
O Shamir, T Zhang
International conference on machine learning, 71-79, 2013
5172013
On the computational efficiency of training neural networks
R Livni, S Shalev-Shwartz, O Shamir
Advances in neural information processing systems 27, 2014
4952014
Communication-efficient distributed optimization using an approximate newton-type method
O Shamir, N Srebro, T Zhang
International conference on machine learning, 1000-1008, 2014
4642014
Size-independent sample complexity of neural networks
N Golowich, A Rakhlin, O Shamir
Conference On Learning Theory, 297-299, 2018
3762018
Better mini-batch algorithms via accelerated gradient methods
A Cotter, O Shamir, N Srebro, K Sridharan
Advances in neural information processing systems 24, 2011
3232011
Adaptively learning the crowd kernel
O Tamuz, C Liu, S Belongie, O Shamir, AT Kalai
arXiv preprint arXiv:1105.1033, 2011
2802011
Nonstochastic multi-armed bandits with graph-structured feedback
N Alon, N Cesa-Bianchi, C Gentile, S Mannor, Y Mansour, O Shamir
SIAM Journal on Computing 46 (6), 1785-1826, 2017
237*2017
Spurious local minima are common in two-layer relu neural networks
I Safran, O Shamir
International conference on machine learning, 4433-4441, 2018
2152018
Learning and generalization with the information bottleneck
O Shamir, S Sabato, N Tishby
Theoretical Computer Science 411 (29-30), 2696-2711, 2010
1962010
Learning to classify with missing and corrupted features
O Dekel, O Shamir
Proceedings of the 25th international conference on Machine learning, 216-223, 2008
1882008
Depth-width tradeoffs in approximating natural functions with neural networks
I Safran, O Shamir
International conference on machine learning, 2979-2987, 2017
173*2017
On the complexity of bandit and derivative-free stochastic convex optimization
O Shamir
Conference on Learning Theory, 3-24, 2013
1712013
Communication complexity of distributed convex learning and optimization
Y Arjevani, O Shamir
Advances in neural information processing systems 28, 2015
1702015
Vox Populi: Collecting High-Quality Labels from a Crowd.
O Dekel, O Shamir
COLT, 2009
1642009
An optimal algorithm for bandit and zero-order convex optimization with two-point feedback
O Shamir
The Journal of Machine Learning Research 18 (1), 1703-1713, 2017
1602017
A stochastic PCA and SVD algorithm with an exponential convergence rate
O Shamir
International conference on machine learning, 144-152, 2015
1602015
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