Still no free lunches: the price to pay for tighter PAC-Bayes bounds

10 October 2019

Papers citing "Still no free lunches: the price to pay for tighter PAC-Bayes bounds"

20 / 20 papers shown

Title
Randomized Pairwise Learning with Adaptive Sampling: A PAC-Bayes Analysis Sijia Zhou Yunwen Lei Ata Kabán 39 0 0 03 Apr 2025
The Generalization Error of Machine Learning Algorithms S. Perlaza Xinying Zou 74 6 0 18 Nov 2024
A note on generalization bounds for losses with finite moments Borja Rodríguez Gálvez Omar Rivasplata Ragnar Thobaben Mikael Skoglund 44 0 0 25 Mar 2024
PAC-Bayes-Chernoff bounds for unbounded losses Ioar Casado Luis A. Ortega A. Masegosa Aritz Pérez Martínez 38 6 0 02 Jan 2024
On the Validation of Gibbs Algorithms: Training Datasets, Test Datasets and their Aggregation S. Perlaza I. Esnaola Gaetan Bisson H. Vincent Poor 24 19 0 21 Jun 2023
More PAC-Bayes bounds: From bounded losses, to losses with general tail behaviors, to anytime validity Borja Rodríguez Gálvez Ragnar Thobaben Mikael Skoglund 48 9 0 21 Jun 2023
On Certified Generalization in Structured Prediction Bastian Boll Christoph Schnörr 29 0 0 15 Jun 2023
Bayesian Learning for Neural Networks: an algorithmic survey M. Magris Alexandros Iosifidis BDL DRL 54 70 0 21 Nov 2022
Empirical Risk Minimization with Relative Entropy Regularization S. Perlaza Gaetan Bisson I. Esnaola Alain Jean-Marie Stefano Rini 24 20 0 12 Nov 2022
A General framework for PAC-Bayes Bounds for Meta-Learning A. Rezazadeh AI4CE 40 4 0 11 Jun 2022
Online PAC-Bayes Learning Maxime Haddouche Benjamin Guedj 29 21 0 31 May 2022
On change of measure inequalities for $f$ -divergences Antoine Picard-Weibel Benjamin Guedj 38 13 0 11 Feb 2022
Empirical Risk Minimization with Relative Entropy Regularization: Optimality and Sensitivity Analysis S. Perlaza Gaetan Bisson I. Esnaola A. Jean-Marie Stefano Rini 20 13 0 09 Feb 2022
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 66 31 0 21 Sep 2021
Free Energy Minimization: A Unified Framework for Modelling, Inference, Learning,and Optimization Sharu Theresa Jose Osvaldo Simeone 13 9 0 25 Nov 2020
Fast-Rate Loss Bounds via Conditional Information Measures with Applications to Neural Networks Fredrik Hellström G. Durisi 51 2 0 22 Oct 2020
Generalization Bounds via Information Density and Conditional Information Density Fredrik Hellström G. Durisi 27 65 0 16 May 2020
Generalization Error Bounds via $m$ th Central Moments of the Information Density Fredrik Hellström G. Durisi 8 5 0 20 Apr 2020
Simpler PAC-Bayesian Bounds for Hostile Data Pierre Alquier Benjamin Guedj 89 72 0 23 Oct 2016
Pac-Bayesian Supervised Classification: The Thermodynamics of Statistical Learning O. Catoni 167 455 0 03 Dec 2007