Waïss Azizian | DeepAI

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∙ 05/26/2023

Exact Generalization Guarantees for (Regularized) Wasserstein Distributionally Robust Models

Wasserstein distributionally robust estimators have emerged as powerful ...

0 Waïss Azizian, et al. ∙

∙ 11/15/2022

On the rate of convergence of Bregman proximal methods in constrained variational inequalities

We examine the last-iterate convergence rate of Bregman proximal methods...

0 Waïss Azizian, et al. ∙

∙ 07/05/2021

The Last-Iterate Convergence Rate of Optimistic Mirror Descent in Stochastic Variational Inequalities

In this paper, we analyze the local convergence rate of optimistic mirro...

0 Waïss Azizian, et al. ∙

∙ 06/28/2020

Characterizing the Expressive Power of Invariant and Equivariant Graph Neural Networks

Various classes of Graph Neural Networks (GNN) have been proposed and sh...

12 Waïss Azizian, et al. ∙

∙ 01/02/2020

Accelerating Smooth Games by Manipulating Spectral Shapes

We use matrix iteration theory to characterize acceleration in smooth ga...

16 Waïss Azizian, et al. ∙

∙ 06/17/2019

Lower Bounds and Conditioning of Differentiable Games

Many recent machine learning tools rely on differentiable game formulati...

0 Adam Ibrahim, et al. ∙

∙ 06/13/2019

A Tight and Unified Analysis of Extragradient for a Whole Spectrum of Differentiable Games

We consider differentiable games: multi-objective minimization problems,...

0 Waïss Azizian, et al. ∙

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