Author

Yishay Mansour

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Preprint Sep 2026

Machine Unlearning as Private Retroactive Algorithms

Machine unlearning typically aims to emulate retraining from scratch: upon a deletion request, the unlearning algorithm should produce an outcome that would have been obtained had the deleted point never been included. Recent work has shown that this emulation requirement carries no meaningful privacy semantics against...

Haim Kaplan, R. Kohen, Yishay Mansour et al. · 0 citations

Preprint Jul 2026

Is Randomness Necessary for Adaptive Data Analysis?

It is shown that randomness is strictly necessary to answer a non-trivial number of adaptive queries: when the analyst is unbounded, any deterministic mechanism can be forced to fail after just $k = \tilde{O}(n)$ queries.

Edith Cohen, Haim Kaplan, Yishay Mansour et al. · 0 citations