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A Primer on PAC-Bayesian Learning

16 January 2019

Papers citing "A Primer on PAC-Bayesian Learning"

50 / 157 papers shown

Title
Position: There Is No Free Bayesian Uncertainty Quantification Ivan Melev Goeran Kauermann UQCV BDL 86 0 0 04 Jun 2025
Proximal optimal transport divergences Ricardo Baptista Panagiota Birmpa Markos A. Katsoulakis Luc Rey-Bellet Benjamin J. Zhang OT 95 0 0 17 May 2025
Kullback-Leibler excess risk bounds for exponential weighted aggregation in Generalized linear models Tien Mai FedML 100 0 0 14 Apr 2025
Optimal sparse phase retrieval via a quasi-Bayesian approach Tien Mai 79 1 0 13 Apr 2025
How good is PAC-Bayes at explaining generalisation? Antoine Picard-Weibel Eugenio Clerico Roman Moscoviz Benjamin Guedj 94 0 0 11 Mar 2025
Deep Learning is Not So Mysterious or Different Andrew Gordon Wilson 101 6 0 03 Mar 2025
Identifying Information from Observations with Uncertainty and Novelty D. Prijatelj Timothy J. Ireland Walter J. Scheirer 125 0 0 16 Jan 2025
High-dimensional prediction for count response via sparse exponential weights The Tien Mai 71 0 0 20 Oct 2024
Learning via Surrogate PAC-Bayes Antoine Picard-Weibel Roman Moscoviz Benjamin Guedj 61 0 0 14 Oct 2024
Online-to-PAC generalization bounds under graph-mixing dependencies Baptiste Abeles Eugenio Clerico Gergely Neu 89 0 0 11 Oct 2024
A Generalization Result for Convergence in Learning-to-Optimize Michael Sucker Peter Ochs 96 0 0 10 Oct 2024
A sparse PAC-Bayesian approach for high-dimensional quantile prediction The Tien Mai 76 3 0 03 Sep 2024
Misclassification excess risk bounds for PAC-Bayesian classification via convexified loss The Tien Mai 95 0 0 16 Aug 2024
Generalization of Hamiltonian algorithms Andreas Maurer 76 1 0 23 May 2024
PAC-Bayesian Generalization Bounds for Knowledge Graph Representation Learning Jaejun Lee Minsung Hwang J. Whang 79 1 0 10 May 2024
Misclassification bounds for PAC-Bayesian sparse deep learning The Tien Mai UQCV BDL 111 4 0 02 May 2024
Leveraging PAC-Bayes Theory and Gibbs Distributions for Generalization Bounds with Complexity Measures Paul Viallard Rémi Emonet Amaury Habrard Emilie Morvant Valentina Zantedeschi 116 3 0 19 Feb 2024
A PAC-Bayesian Link Between Generalisation and Flat Minima Maxime Haddouche Paul Viallard Umut Simsekli Benjamin Guedj 116 4 0 13 Feb 2024
Tighter Generalisation Bounds via Interpolation Paul Viallard Maxime Haddouche Umut Simsekli Benjamin Guedj 81 3 0 07 Feb 2024
More Flexible PAC-Bayesian Meta-Learning by Learning Learning Algorithms Hossein Zakerinia Amin Behjati Christoph H. Lampert FedML 86 7 0 06 Feb 2024
Personalized Federated Learning of Probabilistic Models: A PAC-Bayesian Approach Mahrokh Ghoddousi Boroujeni Andreas Krause Giancarlo Ferrari-Trecate FedML 129 3 0 16 Jan 2024
PAC-Bayes-Chernoff bounds for unbounded losses Ioar Casado Luis A. Ortega A. Masegosa Aritz Pérez Martínez 113 6 0 02 Jan 2024
PAC-Bayesian Domain Adaptation Bounds for Multi-view learning Mehdi Hennequin K. Benabdeslem H. Elghazel 58 0 0 02 Jan 2024
A note on regularised NTK dynamics with an application to PAC-Bayesian training Eugenio Clerico Benjamin Guedj 112 0 0 20 Dec 2023
PAC-Bayes Generalisation Bounds for Dynamical Systems Including Stable RNNs Deividas Eringis J. Leth Zheng-Hua Tan Rafal Wisniewski Mihaly Petreczky 52 3 0 15 Dec 2023
Pseudo-Likelihood Inference Theo Gruner Boris Belousov Fabio Muratore Daniel Palenicek Jan Peters 84 0 0 28 Nov 2023
Time-Uniform Confidence Spheres for Means of Random Vectors Ben Chugg Hongjian Wang Aaditya Ramdas 203 5 0 14 Nov 2023
Data-Efficient Task Generalization via Probabilistic Model-based Meta Reinforcement Learning Arjun Bhardwaj Jonas Rothfuss Bhavya Sukhija Yarden As Marco Hutter Stelian Coros Andreas Krause 90 5 0 13 Nov 2023
Estimating optimal PAC-Bayes bounds with Hamiltonian Monte Carlo Szilvia Ujváry Gergely Flamich Vincent Fortuin José Miguel Hernández Lobato 65 0 0 30 Oct 2023
Graph Neural Networks with a Distribution of Parametrized Graphs See Hian Lee Feng Ji Kelin Xia Wee Peng Tay 72 0 0 25 Oct 2023
Sequential Gibbs Posteriors with Applications to Principal Component Analysis Steven Winter Omar Melikechi David B. Dunson 77 2 0 19 Oct 2023
Federated Learning with Nonvacuous Generalisation Bounds Pierre Jobic Maxime Haddouche Benjamin Guedj FedML 78 4 0 17 Oct 2023
Comparing Comparators in Generalization Bounds Fredrik Hellström Benjamin Guedj 76 4 0 16 Oct 2023
The surrogate Gibbs-posterior of a corrected stochastic MALA: Towards uncertainty quantification for neural networks S. Bieringer Gregor Kasieczka Maximilian F. Steffen Mathias Trabs 92 1 0 13 Oct 2023
Hamiltonian Dynamics of Bayesian Inference Formalised by Arc Hamiltonian Systems Takuo Matsubara 37 0 0 11 Oct 2023
Statistical Guarantees for Variational Autoencoders using PAC-Bayesian Theory S. Mbacke Florence Clerc Pascal Germain DRL 104 13 0 07 Oct 2023
A path-norm toolkit for modern networks: consequences, promises and challenges Antoine Gonon Nicolas Brisebarre E. Riccietti Rémi Gribonval 109 6 0 02 Oct 2023
Improved Algorithms for Stochastic Linear Bandits Using Tail Bounds for Martingale Mixtures H. Flynn David Reeb M. Kandemir Jan Peters 75 9 0 25 Sep 2023
Feature Noise Boosts DNN Generalization under Label Noise Lu Zeng Xuan Chen Xiaoshuang Shi Jikang Cheng MLT NoLa 58 2 0 03 Aug 2023
Learning Expressive Priors for Generalization and Uncertainty Estimation in Neural Networks Dominik Schnaus Jongseok Lee Zorah Lähner Rudolph Triebel UQCV BDL 78 1 0 15 Jul 2023
Transformers in Reinforcement Learning: A Survey Pranav Agarwal A. Rahman P. St-Charles Simon J. D. Prince Samira Ebrahimi Kahou OffRL 108 21 0 12 Jul 2023
Sparsity-aware generalization theory for deep neural networks Ramchandran Muthukumar Jeremias Sulam MLT 58 7 0 01 Jul 2023
On Certified Generalization in Structured Prediction Bastian Boll Christoph Schnörr 62 0 0 15 Jun 2023
MMD-FUSE: Learning and Combining Kernels for Two-Sample Testing Without Data Splitting Felix Biggs Antonin Schrab Arthur Gretton 95 21 0 14 Jun 2023
Learning via Wasserstein-Based High Probability Generalisation Bounds Paul Viallard Maxime Haddouche Umut Simsekli Benjamin Guedj 77 12 0 07 Jun 2023
Enhance Diffusion to Improve Robust Generalization Jianhui Sun Sanchit Sinha Aidong Zhang 79 4 0 05 Jun 2023
Coherent Soft Imitation Learning Joe Watson Sandy H. Huang Nicholas Heess 91 12 0 25 May 2023
Exponential Smoothing for Off-Policy Learning Imad Aouali Victor-Emmanuel Brunel D. Rohde Anna Korba OffRL 82 14 0 25 May 2023
A Rigorous Link between Deep Ensembles and (Variational) Bayesian Methods Veit Wild Sahra Ghalebikesabi Dino Sejdinovic Jeremias Knoblauch BDL UQCV 98 16 0 24 May 2023
Exponential Stochastic Inequality Peter Grünwald M. F. Pérez-Ortiz Zakaria Mhammedi 61 1 0 27 Apr 2023