activity
20192021
most citedMixed Nash Equilibria in the Adversarial Examples Game

2 citations · 2 across the 2 of their papers we have counts for

collaborators

7 papers

stat.ML2021

Low-Rank Sinkhorn Factorization

Meyer Scetbon, Marco Cuturi, Gabriel Peyré

Several recent applications of optimal transport (OT) theory to machine learning have relied on regularization, notably entropy and the Sinkhorn algorithm. Because matrix-vector pr…

cs.GT20212 cited

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…

stat.ML2020

Equitable and Optimal Transport with Multiple Agents

Meyer Scetbon, Laurent Meunier, Jamal Atif +1

We introduce an extension of the Optimal Transport problem when multiple costs are involved. Considering each cost as an agent, we aim to share equally between agents the work of t…

stat.ML2020

Linear Time Sinkhorn Divergences using Positive Features

Meyer Scetbon, Marco Cuturi

Although Sinkhorn divergences are now routinely used in data sciences to compare probability distributions, the computational effort required to compute them remains expensive, gro…

stat.ML2020

Harmonic Decompositions of Convolutional Networks

Meyer Scetbon, Zaid Harchaoui

We present a description of the function space and the smoothness class associated with a convolutional network using the machinery of reproducing kernel Hilbert spaces. We show th…

stat.ML2020

A Spectral Analysis of Dot-product Kernels

Meyer Scetbon, Zaid Harchaoui

We present eigenvalue decay estimates of integral operators associated with compositional dot-product kernels. The estimates improve on previous ones established for power series k…