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PAC-Bayesian Bounds for Randomized Empirical Risk Minimizers

PAC-Bayesian Bounds for Randomized Empirical Risk Minimizers

11 December 2007
Pierre Alquier
ArXivPDFHTML

Papers citing "PAC-Bayesian Bounds for Randomized Empirical Risk Minimizers"

16 / 16 papers shown
Title
Filtered not Mixed: Stochastic Filtering-Based Online Gating for Mixture of Large Language Models
Filtered not Mixed: Stochastic Filtering-Based Online Gating for Mixture of Large Language Models
Raeid Saqur
Anastasis Kratsios
Florian Krach
Yannick Limmer
Jacob-Junqi Tian
John Willes
Blanka Horvath
Frank Rudzicz
MoE
45
0
0
24 Feb 2025
Scalable PAC-Bayesian Meta-Learning via the PAC-Optimal Hyper-Posterior:
  From Theory to Practice
Scalable PAC-Bayesian Meta-Learning via the PAC-Optimal Hyper-Posterior: From Theory to Practice
Jonas Rothfuss
Martin Josifoski
Vincent Fortuin
Andreas Krause
37
7
0
14 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
21
4
0
11 Jun 2022
User-friendly introduction to PAC-Bayes bounds
User-friendly introduction to PAC-Bayes bounds
Pierre Alquier
FedML
51
196
0
21 Oct 2021
Online learning with exponential weights in metric spaces
Online learning with exponential weights in metric spaces
Q. Paris
24
4
0
26 Mar 2021
Gibbs posterior concentration rates under sub-exponential type losses
Gibbs posterior concentration rates under sub-exponential type losses
Nicholas Syring
Ryan Martin
14
29
0
08 Dec 2020
PAC-Bayes Analysis Beyond the Usual Bounds
PAC-Bayes Analysis Beyond the Usual Bounds
Omar Rivasplata
Ilja Kuzborskij
Csaba Szepesvári
John Shawe-Taylor
30
80
0
23 Jun 2020
PAC-Bayesian AUC classification and scoring
PAC-Bayesian AUC classification and scoring
James Ridgway
Pierre Alquier
Nicolas Chopin
Feng Liang
35
21
0
07 Oct 2014
A General Framework for Updating Belief Distributions
A General Framework for Updating Belief Distributions
Pier Giovanni Bissiri
Chris Holmes
S. Walker
46
466
0
27 Jun 2013
Prediction of quantiles by statistical learning and application to GDP
  forecasting
Prediction of quantiles by statistical learning and application to GDP forecasting
Pierre Alquier
Xiaoyin Li
AI4TS
57
14
0
20 Feb 2012
PAC-Bayesian aggregation and multi-armed bandits
PAC-Bayesian aggregation and multi-armed bandits
Jean-Yves Audibert
98
21
0
15 Nov 2010
Linear regression through PAC-Bayesian truncation
Linear regression through PAC-Bayesian truncation
Jean-Yves Audibert
O. Catoni
70
16
0
01 Oct 2010
Mirror averaging with sparsity priors
Mirror averaging with sparsity priors
A. Dalalyan
Alexandre B. Tsybakov
102
59
0
05 Mar 2010
Sparse Regression Learning by Aggregation and Langevin Monte-Carlo
Sparse Regression Learning by Aggregation and Langevin Monte-Carlo
A. Dalalyan
Alexandre B. Tsybakov
101
178
0
06 Mar 2009
Model selection for weakly dependent time series forecasting
Model selection for weakly dependent time series forecasting
Pierre Alquier
Olivier Wintenberger
OOD
AI4TS
73
80
0
17 Feb 2009
Pac-Bayesian Supervised Classification: The Thermodynamics of
  Statistical Learning
Pac-Bayesian Supervised Classification: The Thermodynamics of Statistical Learning
O. Catoni
148
453
0
03 Dec 2007
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