PAC-Bayes-Chernoff bounds for unbounded losses

2 January 2024

Papers citing "PAC-Bayes-Chernoff bounds for unbounded losses"

21 / 21 papers shown

Title
Sample Compression Unleashed: New Generalization Bounds for Real Valued Losses Mathieu Bazinet Valentina Zantedeschi Pascal Germain MLT AI4CE 54 1 0 26 Sep 2024
A PAC-Bayesian Link Between Generalisation and Flat Minima Maxime Haddouche Paul Viallard Umut Simsekli Benjamin Guedj 80 4 0 13 Feb 2024
Generalization Bounds: Perspectives from Information Theory and PAC-Bayes Fredrik Hellström G. Durisi Benjamin Guedj Maxim Raginsky 34 36 0 08 Sep 2023
Bayesian Model Selection, the Marginal Likelihood, and Generalization Sanae Lotfi Pavel Izmailov Gregory W. Benton Micah Goldblum A. Wilson UQCV BDL 94 58 0 23 Feb 2022
Chebyshev-Cantelli PAC-Bayes-Bennett Inequality for the Weighted Majority Vote Yi-Shan Wu A. Masegosa S. Lorenzen Christian Igel Yevgeny Seldin 26 8 0 25 Jun 2021
Information Complexity and Generalization Bounds P. Banerjee Guido Montúfar 34 14 0 04 May 2021
Still no free lunches: the price to pay for tighter PAC-Bayes bounds Benjamin Guedj L. Pujol FedML 52 23 0 10 Oct 2019
Efficient and Accurate Estimation of Lipschitz Constants for Deep Neural Networks Mahyar Fazlyab Alexander Robey Hamed Hassani M. Morari George J. Pappas 87 456 0 12 Jun 2019
PAC-Bayes under potentially heavy tails Matthew J. Holland 62 42 0 20 May 2019
A Primer on PAC-Bayesian Learning Benjamin Guedj 124 222 0 16 Jan 2019
Lipschitz regularity of deep neural networks: analysis and efficient estimation Kevin Scaman Aladin Virmaux 75 527 0 28 May 2018
On the Convergence of Stochastic Gradient Descent with Adaptive Stepsizes Xiaoyun Li Francesco Orabona 67 295 0 21 May 2018
Improving the Adversarial Robustness and Interpretability of Deep Neural Networks by Regularizing their Input Gradients A. Ross Finale Doshi-Velez AAML 147 680 0 26 Nov 2017
A PAC-Bayesian Approach to Spectrally-Normalized Margin Bounds for Neural Networks Behnam Neyshabur Srinadh Bhojanapalli Nathan Srebro 80 605 0 29 Jul 2017
Information-theoretic analysis of generalization capability of learning algorithms Aolin Xu Maxim Raginsky 143 445 0 22 May 2017
Computing Nonvacuous Generalization Bounds for Deep (Stochastic) Neural Networks with Many More Parameters than Training Data Gintare Karolina Dziugaite Daniel M. Roy 103 812 0 31 Mar 2017
Understanding deep learning requires rethinking generalization Chiyuan Zhang Samy Bengio Moritz Hardt Benjamin Recht Oriol Vinyals HAI 314 4,624 0 10 Nov 2016
PAC-Bayesian Theory Meets Bayesian Inference Pascal Germain Francis R. Bach Alexandre Lacoste Simon Lacoste-Julien 65 183 0 27 May 2016
An Oracle Inequality for Quasi-Bayesian Non-Negative Matrix Factorization Pierre Alquier Benjamin Guedj 72 17 0 06 Jan 2016
Rethinking the Inception Architecture for Computer Vision Christian Szegedy Vincent Vanhoucke Sergey Ioffe Jonathon Shlens Z. Wojna 3DV BDL 717 27,303 0 02 Dec 2015
Pac-Bayesian Supervised Classification: The Thermodynamics of Statistical Learning O. Catoni 272 458 0 03 Dec 2007