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Wasserstein PAC-Bayes Learning: Exploiting Optimisation Guarantees to
  Explain Generalisation

Wasserstein PAC-Bayes Learning: Exploiting Optimisation Guarantees to Explain Generalisation

14 April 2023
Maxime Haddouche
Benjamin Guedj
ArXivPDFHTML

Papers citing "Wasserstein PAC-Bayes Learning: Exploiting Optimisation Guarantees to Explain Generalisation"

4 / 4 papers shown
Title
PAC-Bayes Generalisation Bounds for Heavy-Tailed Losses through
  Supermartingales
PAC-Bayes Generalisation Bounds for Heavy-Tailed Losses through Supermartingales
Maxime Haddouche
Benjamin Guedj
40
20
0
03 Oct 2022
Learning PAC-Bayes Priors for Probabilistic Neural Networks
Learning PAC-Bayes Priors for Probabilistic Neural Networks
Maria Perez-Ortiz
Omar Rivasplata
Benjamin Guedj
M. Gleeson
Jingyu Zhang
John Shawe-Taylor
M. Bober
J. Kittler
UQCV
49
31
0
21 Sep 2021
Simpler PAC-Bayesian Bounds for Hostile Data
Simpler PAC-Bayesian Bounds for Hostile Data
Pierre Alquier
Benjamin Guedj
79
72
0
23 Oct 2016
Pac-Bayesian Supervised Classification: The Thermodynamics of
  Statistical Learning
Pac-Bayesian Supervised Classification: The Thermodynamics of Statistical Learning
O. Catoni
135
451
0
03 Dec 2007
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