142 citations · 330 across the 18 of their papers we have counts for
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cs.LG2024
Provable Privacy Attacks on Trained Shallow Neural Networks
Guy Smorodinsky, Gal Vardi, Itay Safran
We study what provable privacy attacks can be shown for trained 2-layer ReLU neural networks, focusing on two types of attacks: membership inference and data reconstruction. We pro…
cs.LG2024
Depth Separations in Neural Networks: Separating the Dimension from the Accuracy
Itay Safran, Daniel Reichman, Paul Valiant
We prove an exponential size separation between depth 2 and depth 3 neural networks (with real inputs), when approximating a -Lipschitz target function to constant…