Beyond Perturbations: Learning Guarantees with Arbitrary Adversarial Test Examples

no code implementations • NeurIPS 2020 • Shafi Goldwasser, Adam Tauman Kalai, Yael Tauman Kalai, Omar Montasser

We present a transductive learning algorithm that takes as input training examples from a distribution $P$ and arbitrary (unlabeled) test examples, possibly chosen by an adversary.

Transductive Learning

The impossibility of obfuscation with auxiliary input or a universal simulator

no code implementations • 1 Jan 2014 • Nir Bitansky, Ran Canetti, Henry Cohn, Shafi Goldwasser, Yael Tauman Kalai, Omer Paneth, Alon Rosen

In particular, we show that indistinguishability obfuscation for all circuits implies: * The impossibility of average-case virtual black box obfuscation with auxiliary input for any circuit family with super-polynomial pseudo-entropy.

Cryptography and Security