Gauthier Gidel

research

∙ 05/30/2023

Synaptic Weight Distributions Depend on the Geometry of Plasticity

Most learning algorithms in machine learning rely on gradient descent to...

0 Roman Pogodin, et al. ∙

research

∙ 05/17/2023

Raising the Bar for Certified Adversarial Robustness with Diffusion Models

Certified defenses against adversarial attacks offer formal guarantees o...

0 Thomas Altstidl, et al. ∙

research

∙ 04/23/2023

Sarah Frank-Wolfe: Methods for Constrained Optimization with Best Rates and Practical Features

The Frank-Wolfe (FW) method is a popular approach for solving optimizati...

0 Aleksandr Beznosikov, et al. ∙

research

∙ 04/14/2023

Performative Prediction with Neural Networks

Performative prediction is a framework for learning models that influenc...

0 Mehrnaz Mofakhami, et al. ∙

research

∙ 02/09/2023

Feature Likelihood Score: Evaluating Generalization of Generative Models Using Samples

Deep generative models have demonstrated the ability to generate complex...

0 Marco Jiralerspong, et al. ∙

research

∙ 11/09/2022

Extragradient with Positive Momentum is Optimal for Games with Cross-Shaped Jacobian Spectrum

The extragradient method has recently gained increasing attention, due t...

0 Junhyung Lyle Kim, et al. ∙

research

∙ 10/31/2022

Nesterov Meets Optimism: Rate-Optimal Optimistic-Gradient-Based Method for Stochastic Bilinearly-Coupled Minimax Optimization

We provide a novel first-order optimization algorithm for bilinearly-cou...

0 Chris Junchi Li, et al. ∙

research

∙ 10/09/2022

Dissecting adaptive methods in GANs

Adaptive methods are a crucial component widely used for training genera...

0 Samy Jelassi, et al. ∙

research

∙ 09/27/2022

The Curse of Unrolling: Rate of Differentiating Through Optimization

Computing the Jacobian of the solution of an optimization problem is a c...

0 Damien Scieur, et al. ∙

research

∙ 07/14/2022

Proceedings of the ICML 2022 Expressive Vocalizations Workshop and Competition: Recognizing, Generating, and Personalizing Vocal Bursts

This is the Proceedings of the ICML Expressive Vocalization (ExVo) Compe...

0 Alice Baird, et al. ∙

research

∙ 06/25/2022

Generating Diverse Vocal Bursts with StyleGAN2 and MEL-Spectrograms

We describe our approach for the generative emotional vocal burst task (...

0 Marco Jiralerspong, et al. ∙

research

∙ 06/21/2022

On the Limitations of Elo: Real-World Games, are Transitive, not Additive

Real-world competitive games, such as chess, go, or StarCraft II, rely o...

18 Quentin Bertrand, et al. ∙

research

∙ 06/20/2022

Only Tails Matter: Average-Case Universality and Robustness in the Convex Regime

The recently developed average-case analysis of optimization methods all...

0 Leonardo Cunha, et al. ∙

research

∙ 06/17/2022

Optimal Extragradient-Based Bilinearly-Coupled Saddle-Point Optimization

We consider the smooth convex-concave bilinearly-coupled saddle-point pr...

0 Simon S. Du, et al. ∙

research

∙ 06/09/2022

A General Framework For Proving The Equivariant Strong Lottery Ticket Hypothesis

The Strong Lottery Ticket Hypothesis (SLTH) stipulates the existence of ...

0 Damien Ferbach, et al. ∙

research

∙ 06/01/2022

Variance Reduction is an Antidote to Byzantines: Better Rates, Weaker Assumptions and Communication Compression as a Cherry on the Top

Byzantine-robustness has been gaining a lot of attention due to the grow...

0 Eduard Gorbunov, et al. ∙

research

∙ 05/03/2022

The ICML 2022 Expressive Vocalizations Workshop and Competition: Recognizing, Generating, and Personalizing Vocal Bursts

The ICML Expressive Vocalization (ExVo) Competition is focused on unders...

21 Alice Baird, et al. ∙

research

∙ 04/16/2022

Beyond L1: Faster and Better Sparse Models with skglm

We propose a new fast algorithm to estimate any sparse generalized linea...

0 Quentin Bertrand, et al. ∙

research

∙ 11/16/2021

Stochastic Extragradient: General Analysis and Improved Rates

The Stochastic Extragradient (SEG) method is one of the most popular alg...

10 Eduard Gorbunov, et al. ∙

research

∙ 11/04/2021

Generating Diverse Realistic Laughter for Interactive Art

We propose an interactive art project to make those rendered invisible b...

0 M. Mehdi Afsar, et al. ∙

research

∙ 10/20/2021

Convergence Analysis and Implicit Regularization of Feedback Alignment for Deep Linear Networks

We theoretically analyze the Feedback Alignment (FA) algorithm, an effic...

0 Manuela Girotti, et al. ∙

research

∙ 10/08/2021

Extragradient Method: O(1/K) Last-Iterate Convergence for Monotone Variational Inequalities and Connections With Cocoercivity

Extragradient method (EG) Korpelevich [1976] is one of the most popular ...

0 Eduard Gorbunov, et al. ∙

research

∙ 10/08/2021

Pick Your Battles: Interaction Graphs as Population-Level Objectives for Strategic Diversity

Strategic diversity is often essential in games: in multi-player games, ...

0 Marta Garnelo, et al. ∙

research

∙ 06/30/2021

Stochastic Gradient Descent-Ascent and Consensus Optimization for Smooth Games: Convergence Analysis under Expected Co-coercivity

Two of the most prominent algorithms for solving unconstrained smooth ga...

6 Nicolas Loizou, et al. ∙

research

∙ 06/30/2021

On the Convergence of Stochastic Extragradient for Bilinear Games with Restarted Iteration Averaging

We study the stochastic bilinear minimax optimization problem, presentin...

1 Chris Junchi Li, et al. ∙

research

∙ 04/08/2021

A single gradient step finds adversarial examples on random two-layers neural networks

Daniely and Schacham recently showed that gradient descent finds adversa...

11 Sébastien Bubeck, et al. ∙

research

∙ 03/02/2021

Online Adversarial Attacks

Adversarial attacks expose important vulnerabilities of deep learning mo...

0 Andjela Mladenovic, et al. ∙

research

∙ 07/01/2020

Adversarial Example Games

The existence of adversarial examples capable of fooling trained neural ...

13 Avishek Joey Bose, et al. ∙

research

∙ 04/20/2020

Real World Games Look Like Spinning Tops

This paper investigates the geometrical properties of real world games (...

10 Wojciech Marian Czarnecki, et al. ∙

research

∙ 02/14/2020

Minimax Theorem for Latent Games or: How I Learned to Stop Worrying about Mixed-Nash and Love Neural Nets

Adversarial training, a special case of multi-objective optimization, is...

0 Gauthier Gidel, et al. ∙

research

∙ 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. ∙

research

∙ 07/09/2019

Finite Regret and Cycles with Fixed Step-Size via Alternating Gradient Descent-Ascent

Gradient descent is arguably one of the most popular online optimization...

0 James P. Bailey, et al. ∙

research

∙ 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. ∙

research

∙ 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. ∙

research

∙ 06/11/2019

A Closer Look at the Optimization Landscapes of Generative Adversarial Networks

Generative adversarial networks have been very successful in generative ...

1 Hugo Berard, et al. ∙

research

∙ 05/28/2019

Non-normal Recurrent Neural Network (nnRNN): learning long time dependencies while improving expressivity with transient dynamics

A recent strategy to circumvent the exploding and vanishing gradient pro...

1 Giancarlo Kerg, et al. ∙

research

∙ 05/24/2019

Painless Stochastic Gradient: Interpolation, Line-Search, and Convergence Rates

Recent works have shown that stochastic gradient descent (SGD) achieves ...

10 Sharan Vaswani, et al. ∙

research

∙ 04/30/2019

Implicit Regularization of Discrete Gradient Dynamics in Deep Linear Neural Networks

When optimizing over-parameterized models, such as deep neural networks,...

2 Gauthier Gidel, et al. ∙

research

∙ 04/18/2019

Reducing Noise in GAN Training with Variance Reduced Extragradient

Using large mini-batches when training generative adversarial networks (...

38 Tatjana Chavdarova, et al. ∙

research

∙ 07/12/2018

Negative Momentum for Improved Game Dynamics

Games generalize the optimization paradigm by introducing different obje...

11 Gauthier Gidel, et al. ∙

research

∙ 04/09/2018

Frank-Wolfe Splitting via Augmented Lagrangian Method

Minimizing a function over an intersection of convex sets is an importan...

0 Gauthier Gidel, et al. ∙

research

∙ 04/06/2018

Adaptive Three Operator Splitting

We propose and analyze a novel adaptive step size variant of the Davis-Y...

0 Fabian Pedregosa, et al. ∙

research

∙ 02/28/2018

A Variational Inequality Perspective on Generative Adversarial Nets

Stability has been a recurrent issue in training generative adversarial ...

0 Gauthier Gidel, et al. ∙

research

∙ 08/08/2017

Parametric Adversarial Divergences are Good Task Losses for Generative Modeling

Generative modeling of high dimensional data like images is a notoriousl...

1 Gabriel Huang, et al. ∙

research

∙ 10/25/2016

Frank-Wolfe Algorithms for Saddle Point Problems

We extend the Frank-Wolfe (FW) optimization algorithm to solve constrain...

0 Gauthier Gidel, et al. ∙

Gauthier Gidel

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