Viallard, Paul

11 publications

ALT 2025 A PAC-Bayesian Link Between Generalisation and Flat Minima Maxime Haddouche, Paul Viallard, Umut Simsekli, Benjamin Guedj

MLJ 2024 A General Framework for the Practical Disintegration of PAC-Bayesian Bounds Paul Viallard, Pascal Germain, Amaury Habrard, Emilie Morvant

ECML-PKDD 2024 A Theoretically Grounded Extension of Universal Attacks from the Attacker's Viewpoint Jordan Patracone, Paul Viallard, Emilie Morvant, Gilles Gasso, Amaury Habrard, Stéphane Canu

AISTATS 2024 Leveraging PAC-Bayes Theory and Gibbs Distributions for Generalization Bounds with Complexity Measures Paul Viallard, Rémi Emonet, Amaury Habrard, Emilie Morvant, Valentina Zantedeschi

JMLR 2024 Uniform Generalization Bounds on Data-Dependent Hypothesis Sets via PAC-Bayesian Theory on Random Sets Benjamin Dupuis, Paul Viallard, George Deligiannidis, Umut Simsekli

NeurIPSW 2023 From Mutual Information to Expected Dynamics: New Generalization Bounds for Heavy-Tailed SGD Benjamin Dupuis, Paul Viallard

NeurIPS 2023 Learning via Wasserstein-Based High Probability Generalisation Bounds Paul Viallard, Maxime Haddouche, Umut Simsekli, Benjamin Guedj

NeurIPSW 2023 Learning via Wasserstein-Based High Probability Generalisation Bounds Paul Viallard, Maxime Haddouche, Umut Simsekli, Benjamin Guedj

NeurIPS 2021 A PAC-Bayes Analysis of Adversarial Robustness Paul Viallard, Eric Guillaume Vidot, Amaury Habrard, Emilie Morvant

NeurIPS 2021 Learning Stochastic Majority Votes by Minimizing a PAC-Bayes Generalization Bound Valentina Zantedeschi, Paul Viallard, Emilie Morvant, Rémi Emonet, Amaury Habrard, Pascal Germain, Benjamin Guedj

ECML-PKDD 2021 Self-Bounding Majority Vote Learning Algorithms by the Direct Minimization of a Tight PAC-Bayesian C-Bound Paul Viallard, Pascal Germain, Amaury Habrard, Emilie Morvant