Entropy-SGD optimizes the prior of a PAC-Bayes bound: Generalization properties of Entropy-SGD and data-dependent priors

26 December 2017

Papers citing "Entropy-SGD optimizes the prior of a PAC-Bayes bound: Generalization properties of Entropy-SGD and data-dependent priors"

36 / 36 papers shown

Title
Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Milad Sefidgaran Abdellatif Zaidi Piotr Krasnowski 44 0 0 25 Apr 2025
Generalization Guarantees for Representation Learning via Data-Dependent Gaussian Mixture Priors Milad Sefidgaran A. Zaidi Piotr Krasnowski 91 1 0 21 Feb 2025
Sample Compression Unleashed: New Generalization Bounds for Real Valued Losses Mathieu Bazinet Valentina Zantedeschi Pascal Germain MLT AI4CE 31 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 39 3 0 19 Feb 2024
Personalized Federated Learning of Probabilistic Models: A PAC-Bayesian Approach Mahrokh Ghoddousi Boroujeni Andreas Krause Giancarlo Ferrari-Trecate FedML 32 3 0 16 Jan 2024
More PAC-Bayes bounds: From bounded losses, to losses with general tail behaviors, to anytime validity Borja Rodríguez Gálvez Ragnar Thobaben Mikael Skoglund 28 9 0 21 Jun 2023
On Certified Generalization in Structured Prediction Bastian Boll Christoph Schnörr 21 0 0 15 Jun 2023
Practicality of generalization guarantees for unsupervised domain adaptation with neural networks Adam Breitholtz Fredrik D. Johansson OOD 21 1 0 15 Mar 2023
Scalable PAC-Bayesian Meta-Learning via the PAC-Optimal Hyper-Posterior: From Theory to Practice Jonas Rothfuss Martin Josifoski Vincent Fortuin Andreas Krause 40 7 0 14 Nov 2022
Instance-Dependent Generalization Bounds via Optimal Transport Songyan Hou Parnian Kassraie Anastasis Kratsios Andreas Krause Jonas Rothfuss 22 6 0 02 Nov 2022
A PAC-Bayesian Generalization Bound for Equivariant Networks Arash Behboodi Gabriele Cesa Taco S. Cohen 53 17 0 24 Oct 2022
Enhancing Adversarial Training with Second-Order Statistics of Weights Gao Jin Xinping Yi Wei Huang S. Schewe Xiaowei Huang AAML 26 47 0 11 Mar 2022
Generalization Through The Lens Of Leave-One-Out Error Gregor Bachmann Thomas Hofmann Aurelien Lucchi 49 7 0 07 Mar 2022
Adversarial robustness of sparse local Lipschitz predictors Ramchandran Muthukumar Jeremias Sulam AAML 32 13 0 26 Feb 2022
Anticorrelated Noise Injection for Improved Generalization Antonio Orvieto Hans Kersting F. Proske Francis R. Bach Aurelien Lucchi 53 44 0 06 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
Self-Certifying Classification by Linearized Deep Assignment Bastian Boll Alexander Zeilmann Stefania Petra Christoph Schnörr 11 2 0 26 Jan 2022
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 17 0 0 28 Oct 2021
Does the Data Induce Capacity Control in Deep Learning? Rubing Yang J. Mao Pratik Chaudhari 25 15 0 27 Oct 2021
Probabilistic fine-tuning of pruning masks and PAC-Bayes self-bounded learning Soufiane Hayou Bo He Gintare Karolina Dziugaite 37 2 0 22 Oct 2021
User-friendly introduction to PAC-Bayes bounds Pierre Alquier FedML 60 196 0 21 Oct 2021
Ridgeless Interpolation with Shallow ReLU Networks in $1D$ is Nearest Neighbor Curvature Extrapolation and Provably Generalizes on Lipschitz Functions Boris Hanin MLT 38 9 0 27 Sep 2021
Unveiling the structure of wide flat minima in neural networks Carlo Baldassi Clarissa Lauditi Enrico M. Malatesta Gabriele Perugini R. Zecchina 11 32 0 02 Jul 2021
A unified PAC-Bayesian framework for machine unlearning via information risk minimization Sharu Theresa Jose Osvaldo Simeone MU 11 7 0 01 Jun 2021
NeurIPS 2020 Competition: Predicting Generalization in Deep Learning Yiding Jiang Pierre Foret Scott Yak Daniel M. Roy H. Mobahi Gintare Karolina Dziugaite Samy Bengio Suriya Gunasekar Isabelle M Guyon Behnam Neyshabur Google Research OOD 24 55 0 14 Dec 2020
A Bayesian Perspective on Training Speed and Model Selection Clare Lyle Lisa Schut Binxin Ru Y. Gal Mark van der Wilk 39 24 0 27 Oct 2020
PAC-Bayes Analysis Beyond the Usual Bounds Omar Rivasplata Ilja Kuzborskij Csaba Szepesvári John Shawe-Taylor 30 80 0 23 Jun 2020
Information-Theoretic Generalization Bounds for SGLD via Data-Dependent Estimates Jeffrey Negrea Mahdi Haghifam Gintare Karolina Dziugaite Ashish Khisti Daniel M. Roy FedML 110 147 0 06 Nov 2019
PAC-Bayes with Backprop Omar Rivasplata Vikram Tankasali Csaba Szepesvári 21 49 0 19 Aug 2019
Chaining Meets Chain Rule: Multilevel Entropic Regularization and Training of Neural Nets Amir-Reza Asadi Emmanuel Abbe BDL AI4CE 34 13 0 26 Jun 2019
Data-dependent Sample Complexity of Deep Neural Networks via Lipschitz Augmentation Colin Wei Tengyu Ma 12 109 0 09 May 2019
Wireless Network Intelligence at the Edge Jihong Park S. Samarakoon M. Bennis Mérouane Debbah 19 518 0 07 Dec 2018
PAC-Bayes Control: Learning Policies that Provably Generalize to Novel Environments Anirudha Majumdar M. Goldstein Anoopkumar Sonar 20 18 0 11 Jun 2018
Norm-Based Capacity Control in Neural Networks Behnam Neyshabur Ryota Tomioka Nathan Srebro 119 577 0 27 Feb 2015
Pac-Bayesian Supervised Classification: The Thermodynamics of Statistical Learning O. Catoni 148 454 0 03 Dec 2007