2 citations · 2 across the 9 of their papers we have counts for
4 papers · 1 filter
Machine Unlearning as Private Retroactive Algorithms
Haim Kaplan, Refael Kohen, Yishay Mansour +2
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…
Is Randomness Necessary for Adaptive Data Analysis?
Edith Cohen, Haim Kaplan, Yishay Mansour +2
The Adaptive Data Analysis (ADA) problem formalizes the challenge of preventing false discovery and overfitting when a dataset is repeatedly reused. Formally, our input is a datase…
Bayesian Perspective on Memorization and Reconstruction
Haim Kaplan, Yishay Mansour, Kobbi Nissim +1
We introduce a new Bayesian perspective on the concept of data reconstruction, and leverage this viewpoint to propose a new security definition that, in certain settings, provably…
Data Reconstruction: When You See It and When You Don't
Edith Cohen, Haim Kaplan, Yishay Mansour +4
We revisit the fundamental question of formally defining what constitutes a reconstruction attack. While often clear from the context, our exploration reveals that a precise defini…