35 citations · 148 across the 31 of their papers we have counts for
4 papers · 1 filter
Combining Differential Privacy and Byzantine Resilience in Distributed SGD
Rachid Guerraoui, Nirupam Gupta, Rafael Pinot +2
Privacy and Byzantine resilience (BR) are two crucial requirements of modern-day distributed machine learning. The two concepts have been extensively studied individually but the q…
On the robustness of randomized classifiers to adversarial examples
Rafael Pinot, Laurent Meunier, Florian Yger +3
This paper investigates the theory of robustness against adversarial attacks. We focus on randomized classifiers (\emph{i.e.} classifiers that output random variables) and provide…
Mixed Nash Equilibria in the Adversarial Examples Game
Laurent Meunier, Meyer Scetbon, Rafael Pinot +2
This paper tackles the problem of adversarial examples from a game theoretic point of view. We study the open question of the existence of mixed Nash equilibria in the zero-sum gam…
Differential Privacy and Byzantine Resilience in SGD: Do They Add Up?
Rachid Guerraoui, Nirupam Gupta, Rafaël Pinot +2
This paper addresses the problem of combining Byzantine resilience with privacy in machine learning (ML). Specifically, we study if a distributed implementation of the renowned Sto…