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

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

10 October 2019
Benjamin Guedj
L. Pujol
    FedML
ArXiv (abs)PDFHTML

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

17 / 17 papers shown
Title
Randomized Pairwise Learning with Adaptive Sampling: A PAC-Bayes Analysis
Randomized Pairwise Learning with Adaptive Sampling: A PAC-Bayes Analysis
Sijia Zhou
Yunwen Lei
Ata Kabán
146
0
0
03 Apr 2025
The Generalization Error of Machine Learning Algorithms
The Generalization Error of Machine Learning Algorithms
S. Perlaza
Xinying Zou
118
6
0
18 Nov 2024
A note on generalization bounds for losses with finite moments
A note on generalization bounds for losses with finite moments
Borja Rodríguez Gálvez
Omar Rivasplata
Ragnar Thobaben
Mikael Skoglund
63
0
0
25 Mar 2024
PAC-Bayes-Chernoff bounds for unbounded losses
PAC-Bayes-Chernoff bounds for unbounded losses
Ioar Casado
Luis A. Ortega
A. Masegosa
Aritz Pérez Martínez
113
6
0
02 Jan 2024
On the Validation of Gibbs Algorithms: Training Datasets, Test Datasets
  and their Aggregation
On the Validation of Gibbs Algorithms: Training Datasets, Test Datasets and their Aggregation
S. Perlaza
I. Esnaola
Gaetan Bisson
H. Vincent Poor
59
22
0
21 Jun 2023
More PAC-Bayes bounds: From bounded losses, to losses with general tail
  behaviors, to anytime validity
More PAC-Bayes bounds: From bounded losses, to losses with general tail behaviors, to anytime validity
Borja Rodríguez Gálvez
Ragnar Thobaben
Mikael Skoglund
154
9
0
21 Jun 2023
On Certified Generalization in Structured Prediction
On Certified Generalization in Structured Prediction
Bastian Boll
Christoph Schnörr
60
0
0
15 Jun 2023
Bayesian Learning for Neural Networks: an algorithmic survey
Bayesian Learning for Neural Networks: an algorithmic survey
M. Magris
Alexandros Iosifidis
BDLDRL
123
77
0
21 Nov 2022
Empirical Risk Minimization with Relative Entropy Regularization
Empirical Risk Minimization with Relative Entropy Regularization
S. Perlaza
Gaetan Bisson
I. Esnaola
Alain Jean-Marie
Stefano Rini
66
23
0
12 Nov 2022
A General framework for PAC-Bayes Bounds for Meta-Learning
A General framework for PAC-Bayes Bounds for Meta-Learning
A. Rezazadeh
AI4CE
83
4
0
11 Jun 2022
Online PAC-Bayes Learning
Online PAC-Bayes Learning
Maxime Haddouche
Benjamin Guedj
107
22
0
31 May 2022
On change of measure inequalities for $f$-divergences
On change of measure inequalities for fff-divergences
Antoine Picard-Weibel
Benjamin Guedj
76
13
0
11 Feb 2022
Empirical Risk Minimization with Relative Entropy Regularization:
  Optimality and Sensitivity Analysis
Empirical Risk Minimization with Relative Entropy Regularization: Optimality and Sensitivity Analysis
S. Perlaza
Gaetan Bisson
I. Esnaola
A. Jean-Marie
Stefano Rini
62
14
0
09 Feb 2022
Free Energy Minimization: A Unified Framework for Modelling, Inference,
  Learning,and Optimization
Free Energy Minimization: A Unified Framework for Modelling, Inference, Learning,and Optimization
Sharu Theresa Jose
Osvaldo Simeone
51
9
0
25 Nov 2020
Fast-Rate Loss Bounds via Conditional Information Measures with
  Applications to Neural Networks
Fast-Rate Loss Bounds via Conditional Information Measures with Applications to Neural Networks
Fredrik Hellström
G. Durisi
99
2
0
22 Oct 2020
Generalization Bounds via Information Density and Conditional
  Information Density
Generalization Bounds via Information Density and Conditional Information Density
Fredrik Hellström
G. Durisi
132
67
0
16 May 2020
Generalization Error Bounds via $m$th Central Moments of the Information
  Density
Generalization Error Bounds via mmmth Central Moments of the Information Density
Fredrik Hellström
G. Durisi
69
5
0
20 Apr 2020
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