Paul Viallard

Publication Activity (10 Years)

Years Active: 2021-2024
Publications (10 Years): 16

Top Topics

Generalization Bounds

Statistical Learning Theory

Top Venues

Publications

Paul Viallard, Pascal Germain, Amaury Habrard, Emilie Morvant
A general framework for the practical disintegration of PAC-Bayesian bounds. Mach. Learn. 113 (2) (2024)
Benjamin Dupuis, Paul Viallard, George Deligiannidis, Umut Simsekli
Uniform Generalization Bounds on Data-Dependent Hypothesis Sets via PAC-Bayesian Theory on Random Sets. CoRR (2024)
Paul Viallard, Rémi Emonet, Amaury Habrard, Emilie Morvant, Valentina Zantedeschi
Leveraging PAC-Bayes Theory and Gibbs Distributions for Generalization Bounds with Complexity Measures. AISTATS (2024)
Maxime Haddouche, Paul Viallard, Umut Simsekli, Benjamin Guedj
A PAC-Bayesian Link Between Generalisation and Flat Minima. CoRR (2024)
Paul Viallard, Maxime Haddouche, Umut Simsekli, Benjamin Guedj
Tighter Generalisation Bounds via Interpolation. CoRR (2024)
Paul Viallard, Rémi Emonet, Amaury Habrard, Emilie Morvant, Valentina Zantedeschi
Leveraging PAC-Bayes Theory and Gibbs Distributions for Generalization Bounds with Complexity Measures. CoRR (2024)
Paul Viallard, Maxime Haddouche, Umut Simsekli, Benjamin Guedj
Learning via Wasserstein-Based High Probability Generalisation Bounds. NeurIPS (2023)
Paul Viallard, Maxime Haddouche, Umut Simsekli, Benjamin Guedj
Learning via Wasserstein-Based High Probability Generalisation Bounds. CoRR (2023)
Benjamin Dupuis, Paul Viallard
From Mutual Information to Expected Dynamics: New Generalization Bounds for Heavy-Tailed SGD. CoRR (2023)
Valentina Zantedeschi, Paul Viallard, Emilie Morvant, Rémi Emonet, Amaury Habrard, Pascal Germain, Benjamin Guedj
Learning Stochastic Majority Votes by Minimizing a PAC-Bayes Generalization Bound. NeurIPS (2021)
Guillaume Vidot, Paul Viallard, Amaury Habrard, Emilie Morvant
A PAC-Bayes Analysis of Adversarial Robustness. CoRR (2021)
Paul Viallard, Pascal Germain, Amaury Habrard, Emilie Morvant
Self-bounding Majority Vote Learning Algorithms by the Direct Minimization of a Tight PAC-Bayesian C-Bound. ECML/PKDD (2) (2021)
Paul Viallard, Guillaume Vidot, Amaury Habrard, Emilie Morvant
A PAC-Bayes Analysis of Adversarial Robustness. NeurIPS (2021)
Valentina Zantedeschi, Paul Viallard, Emilie Morvant, Rémi Emonet, Amaury Habrard, Pascal Germain, Benjamin Guedj
Learning Stochastic Majority Votes by Minimizing a PAC-Bayes Generalization Bound. CoRR (2021)
Paul Viallard, Pascal Germain, Amaury Habrard, Emilie Morvant
A General Framework for the Derandomization of PAC-Bayesian Bounds. CoRR (2021)
Paul Viallard, Pascal Germain, Amaury Habrard, Emilie Morvant
Self-Bounding Majority Vote Learning Algorithms by the Direct Minimization of a Tight PAC-Bayesian C-Bound. CoRR (2021)