Dichotomize and Generalize: PAC-Bayesian Binary Activated Deep Neural Networks

24 May 2019

Papers citing "Dichotomize and Generalize: PAC-Bayesian Binary Activated Deep Neural Networks"

42 / 42 papers shown

Title
Unlocking the Potential of Text-to-Image Diffusion with PAC-Bayesian Theory Eric H. Jiang Yasi Zhang Zhi Zhang Yixin Wan Andrew Lizarraga Shufan Li Ying Nian Wu DiffM 77 1 0 25 Nov 2024
Sample Compression Unleashed: New Generalization Bounds for Real Valued Losses Mathieu Bazinet Valentina Zantedeschi Pascal Germain MLT AI4CE 29 2 0 26 Sep 2024
Leveraging PAC-Bayes Theory and Gibbs Distributions for Generalization Bounds with Complexity Measures Paul Viallard Rémi Emonet Amaury Habrard Emilie Morvant Valentina Zantedeschi 31 3 0 19 Feb 2024
A note on regularised NTK dynamics with an application to PAC-Bayesian training Eugenio Clerico Benjamin Guedj 33 0 0 20 Dec 2023
Federated Learning with Nonvacuous Generalisation Bounds Pierre Jobic Maxime Haddouche Benjamin Guedj FedML 22 3 0 17 Oct 2023
Comparing Comparators in Generalization Bounds Fredrik Hellström Benjamin Guedj 23 4 0 16 Oct 2023
Learning via Wasserstein-Based High Probability Generalisation Bounds Paul Viallard Maxime Haddouche Umut Simsekli Benjamin Guedj 30 12 0 07 Jun 2023
Wasserstein PAC-Bayes Learning: Exploiting Optimisation Guarantees to Explain Generalisation Maxime Haddouche Benjamin Guedj 25 0 0 14 Apr 2023
A unified recipe for deriving (time-uniform) PAC-Bayes bounds Ben Chugg Hongjian Wang Aaditya Ramdas 19 24 0 07 Feb 2023
PAC-Bayes Bounds for Bandit Problems: A Survey and Experimental Comparison H. Flynn David Reeb M. Kandemir Jan Peters OffRL 11 7 0 29 Nov 2022
PAC-Bayesian Offline Contextual Bandits With Guarantees Otmane Sakhi Pierre Alquier Nicolas Chopin OffRL 19 12 0 24 Oct 2022
Tighter PAC-Bayes Generalisation Bounds by Leveraging Example Difficulty Felix Biggs Benjamin Guedj 18 7 0 20 Oct 2022
PAC-Bayes Generalisation Bounds for Heavy-Tailed Losses through Supermartingales Maxime Haddouche Benjamin Guedj 48 20 0 03 Oct 2022
Seeking Interpretability and Explainability in Binary Activated Neural Networks Benjamin Leblanc Pascal Germain FAtt 29 1 0 07 Sep 2022
Generalisation under gradient descent via deterministic PAC-Bayes Eugenio Clerico Tyler Farghly George Deligiannidis Benjamin Guedj Arnaud Doucet 23 4 0 06 Sep 2022
On Margins and Generalisation for Voting Classifiers Felix Biggs Valentina Zantedeschi Benjamin Guedj 25 8 0 09 Jun 2022
Enhancing Adversarial Training with Second-Order Statistics of Weights Gao Jin Xinping Yi Wei Huang S. Schewe Xiaowei Huang AAML 12 47 0 11 Mar 2022
On PAC-Bayesian reconstruction guarantees for VAEs Badr-Eddine Chérief-Abdellatif Yuyang Shi Arnaud Doucet Benjamin Guedj DRL 45 17 0 23 Feb 2022
On change of measure inequalities for $f$ -divergences Antoine Picard-Weibel Benjamin Guedj 25 13 0 11 Feb 2022
Controlling Multiple Errors Simultaneously with a PAC-Bayes Bound Reuben Adams John Shawe-Taylor Benjamin Guedj 14 2 0 11 Feb 2022
Demystify Optimization and Generalization of Over-parameterized PAC-Bayesian Learning Wei Huang Chunrui Liu Yilan Chen Tianyu Liu R. Xu BDL MLT 19 2 0 04 Feb 2022
Non-Vacuous Generalisation Bounds for Shallow Neural Networks Felix Biggs Benjamin Guedj BDL 30 26 0 03 Feb 2022
Weight Expansion: A New Perspective on Dropout and Generalization Gao Jin Xinping Yi Pengfei Yang Lijun Zhang S. Schewe Xiaowei Huang 27 5 0 23 Jan 2022
Risk bounds for aggregated shallow neural networks using Gaussian prior L. Tinsi A. Dalalyan BDL 12 7 0 21 Dec 2021
PAC-Bayesian Learning of Aggregated Binary Activated Neural Networks with Probabilities over Representations Louis Fortier-Dubois Gaël Letarte Benjamin Leblanc Franccois Laviolette Pascal Germain UQCV 14 0 0 28 Oct 2021
Conditionally Gaussian PAC-Bayes Eugenio Clerico George Deligiannidis Arnaud Doucet 27 10 0 22 Oct 2021
User-friendly introduction to PAC-Bayes bounds Pierre Alquier FedML 34 196 0 21 Oct 2021
Multi-class Probabilistic Bounds for Self-learning Vasilii Feofanov Emilie Devijver Massih-Reza Amini 27 3 0 29 Sep 2021
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 51 31 0 21 Sep 2021
On Margins and Derandomisation in PAC-Bayes Felix Biggs Benjamin Guedj 12 20 0 08 Jul 2021
Chebyshev-Cantelli PAC-Bayes-Bennett Inequality for the Weighted Majority Vote Yi-Shan Wu A. Masegosa S. Lorenzen Christian Igel Yevgeny Seldin 14 8 0 25 Jun 2021
Wide stochastic networks: Gaussian limit and PAC-Bayesian training Eugenio Clerico George Deligiannidis Arnaud Doucet 20 11 0 17 Jun 2021
Upper and Lower Bounds on the Performance of Kernel PCA Maxime Haddouche Benjamin Guedj John Shawe-Taylor 19 4 0 18 Dec 2020
A PAC-Bayesian Perspective on Structured Prediction with Implicit Loss Embeddings Théophile Cantelobre Benjamin Guedj Maria Perez-Ortiz John Shawe-Taylor 11 3 0 07 Dec 2020
Fast-Rate Loss Bounds via Conditional Information Measures with Applications to Neural Networks Fredrik Hellström G. Durisi 40 2 0 22 Oct 2020
Tighter risk certificates for neural networks Maria Perez-Ortiz Omar Rivasplata John Shawe-Taylor Csaba Szepesvári UQCV 4 102 0 25 Jul 2020
Differentiable PAC-Bayes Objectives with Partially Aggregated Neural Networks Felix Biggs Benjamin Guedj FedML UQCV BDL 6 34 0 22 Jun 2020
PAC-Bayesian Generalization Bounds for MultiLayer Perceptrons Xinjie Lan Xin Guo Kenneth Barner 12 3 0 16 Jun 2020
PAC-Bayesian Contrastive Unsupervised Representation Learning Kento Nozawa Pascal Germain Benjamin Guedj SSL BDL 11 26 0 10 Oct 2019
Generalized Variational Inference: Three arguments for deriving new Posteriors Jeremias Knoblauch Jack Jewson Theodoros Damoulas DRL BDL 23 104 0 03 Apr 2019
Normalized Flat Minima: Exploring Scale Invariant Definition of Flat Minima for Neural Networks using PAC-Bayesian Analysis Yusuke Tsuzuku Issei Sato Masashi Sugiyama 14 74 0 15 Jan 2019
Pac-Bayesian Supervised Classification: The Thermodynamics of Statistical Learning O. Catoni 139 453 0 03 Dec 2007