142 citations · 330 across the 18 of their papers we have counts for
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cs.LG2019★ 5 cited
How Good is SGD with Random Shuffling?
Itay Safran, Ohad Shamir
We study the performance of stochastic gradient descent (SGD) on smooth and strongly-convex finite-sum optimization problems. In contrast to the majority of existing theoretical wo…
cs.LG2019
Depth Separations in Neural Networks: What is Actually Being Separated?
Itay Safran, Ronen Eldan, Ohad Shamir
Existing depth separation results for constant-depth networks essentially show that certain radial functions in , which can be easily approximated with depth netw…
cs.LG2019★ 70 cited
A Simple Explanation for the Existence of Adversarial Examples with Small Hamming Distance
Adi Shamir, Itay Safran, Eyal Ronen +1
The existence of adversarial examples in which an imperceptible change in the input can fool well trained neural networks was experimentally discovered by Szegedy et al in 2013, wh…