Paul Viallard
Orcid: 0000-0003-4836-0809
According to our database1,
Paul Viallard
authored at least 12 papers
between 2021 and 2024.
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Bibliography
2024
Mach. Learn., February, 2024
Uniform Generalization Bounds on Data-Dependent Hypothesis Sets via PAC-Bayesian Theory on Random Sets.
CoRR, 2024
Leveraging PAC-Bayes Theory and Gibbs Distributions for Generalization Bounds with Complexity Measures.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024
2023
From Mutual Information to Expected Dynamics: New Generalization Bounds for Heavy-Tailed SGD.
CoRR, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
2022
PAC-Bayesian Bounds and Beyond: Self-Bounding Algorithms and New Perspectives on Generalization in Machine Learning. (Bornes PAC-Bayésiennes et Au-delà: Algorithmes Auto-limitatifs et Nouvelles Perspectives sur la Généralisation en Apprentissage Automatique).
PhD thesis, 2022
2021
Self-bounding Majority Vote Learning Algorithms by the Direct Minimization of a Tight PAC-Bayesian C-Bound.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021