User-friendly introduction to PAC-Bayes bounds

21 October 2021

Papers citing "User-friendly introduction to PAC-Bayes bounds"

50 / 159 papers shown

Title
Tighter Generalisation Bounds via Interpolation Paul Viallard Maxime Haddouche Umut Simsekli Benjamin Guedj 11 3 0 07 Feb 2024
More Flexible PAC-Bayesian Meta-Learning by Learning Learning Algorithms Hossein Zakerinia Amin Behjati Christoph H. Lampert FedML 22 4 0 06 Feb 2024
Generalization and Informativeness of Conformal Prediction Matteo Zecchin Sangwoo Park Osvaldo Simeone Fredrik Hellström 34 6 0 22 Jan 2024
PAC-Bayes-Chernoff bounds for unbounded losses Ioar Casado Luis A. Ortega A. Masegosa Aritz Pérez Martínez 29 6 0 02 Jan 2024
PAC-Bayesian Domain Adaptation Bounds for Multi-view learning Mehdi Hennequin K. Benabdeslem H. Elghazel 28 0 0 02 Jan 2024
A note on regularised NTK dynamics with an application to PAC-Bayesian training Eugenio Clerico Benjamin Guedj 33 0 0 20 Dec 2023
PAC-Bayes Generalisation Bounds for Dynamical Systems Including Stable RNNs Deividas Eringis J. Leth Zheng-Hua Tan Rafal Wisniewski M. Petreczky 17 3 0 15 Dec 2023
A Note on the Convergence of Denoising Diffusion Probabilistic Models S. Mbacke Omar Rivasplata DiffM 21 5 0 10 Dec 2023
Perspectives on the State and Future of Deep Learning - 2023 Micah Goldblum A. Anandkumar Richard Baraniuk Tom Goldstein Kyunghyun Cho Zachary Chase Lipton Melanie Mitchell Preetum Nakkiran Max Welling Andrew Gordon Wilson 55 4 0 07 Dec 2023
From Mutual Information to Expected Dynamics: New Generalization Bounds for Heavy-Tailed SGD Benjamin Dupuis Paul Viallard 18 3 0 01 Dec 2023
Time-Uniform Confidence Spheres for Means of Random Vectors Ben Chugg Hongjian Wang Aaditya Ramdas 43 5 0 14 Nov 2023
A PAC-Bayesian Perspective on the Interpolating Information Criterion Liam Hodgkinson Christopher van der Heide Roberto Salomone Fred Roosta Michael W. Mahoney 35 1 0 13 Nov 2023
Information-Theoretic Generalization Bounds for Transductive Learning and its Applications Huayi Tang Yong Liu 57 1 0 08 Nov 2023
Sample-Conditioned Hypothesis Stability Sharpens Information-Theoretic Generalization Bounds Ziqiao Wang Yongyi Mao 22 5 0 31 Oct 2023
Estimating optimal PAC-Bayes bounds with Hamiltonian Monte Carlo Szilvia Ujváry Gergely Flamich Vincent Fortuin José Miguel Hernández Lobato 20 0 0 30 Oct 2023
Beyond Bayesian Model Averaging over Paths in Probabilistic Programs with Stochastic Support Tim Reichelt C.-H. Luke Ong Tom Rainforth 27 0 0 23 Oct 2023
Federated Learning with Nonvacuous Generalisation Bounds Pierre Jobic Maxime Haddouche Benjamin Guedj FedML 27 3 0 17 Oct 2023
Comparing Comparators in Generalization Bounds Fredrik Hellström Benjamin Guedj 23 4 0 16 Oct 2023
Statistical guarantees for stochastic Metropolis-Hastings S. Bieringer Gregor Kasieczka Maximilian F. Steffen Mathias Trabs 28 1 0 13 Oct 2023
Statistical Guarantees for Variational Autoencoders using PAC-Bayesian Theory S. Mbacke Florence Clerc Pascal Germain DRL 20 10 0 07 Oct 2023
A path-norm toolkit for modern networks: consequences, promises and challenges Antoine Gonon Nicolas Brisebarre E. Riccietti Rémi Gribonval 24 6 0 02 Oct 2023
Importance-Weighted Offline Learning Done Right Germano Gabbianelli Gergely Neu Matteo Papini OffRL 19 5 0 27 Sep 2023
Improved Algorithms for Stochastic Linear Bandits Using Tail Bounds for Martingale Mixtures H. Flynn David Reeb M. Kandemir Jan Peters 21 6 0 25 Sep 2023
Learning to Warm-Start Fixed-Point Optimization Algorithms Rajiv Sambharya Georgina Hall Brandon Amos Bartolomeo Stellato 30 12 0 14 Sep 2023
Information-theoretic Analysis of Test Data Sensitivity in Uncertainty Futoshi Futami Tomoharu Iwata UD PER 17 3 0 23 Jul 2023
Minimax Excess Risk of First-Order Methods for Statistical Learning with Data-Dependent Oracles Kevin Scaman Mathieu Even B. L. Bars Laurent Massoulié 9 1 0 10 Jul 2023
BOF-UCB: A Bayesian-Optimistic Frequentist Algorithm for Non-Stationary Contextual Bandits Nicklas Werge Abdullah Akgul M. Kandemir 35 0 0 07 Jul 2023
Sparsity-aware generalization theory for deep neural networks Ramchandran Muthukumar Jeremias Sulam MLT 16 4 0 01 Jul 2023
Local Risk Bounds for Statistical Aggregation Jaouad Mourtada Tomas Vavskevivcius Nikita Zhivotovskiy 22 1 0 29 Jun 2023
More PAC-Bayes bounds: From bounded losses, to losses with general tail behaviors, to anytime validity Borja Rodríguez Gálvez Ragnar Thobaben Mikael Skoglund 26 9 0 21 Jun 2023
On Certified Generalization in Structured Prediction Bastian Boll Christoph Schnörr 21 0 0 15 Jun 2023
MMD-FUSE: Learning and Combining Kernels for Two-Sample Testing Without Data Splitting Felix Biggs Antonin Schrab A. Gretton 17 19 0 14 Jun 2023
Lessons from Generalization Error Analysis of Federated Learning: You May Communicate Less Often! Milad Sefidgaran Romain Chor A. Zaidi Yijun Wan FedML 27 6 0 09 Jun 2023
Improved Stability and Generalization Guarantees of the Decentralized SGD Algorithm B. L. Bars A. Bellet Marc Tommasi Kevin Scaman Giovanni Neglia 16 1 0 05 Jun 2023
Decentralized SGD and Average-direction SAM are Asymptotically Equivalent Tongtian Zhu Fengxiang He Kaixuan Chen Mingli Song Dacheng Tao 34 15 0 05 Jun 2023
Exponential Smoothing for Off-Policy Learning Imad Aouali Victor-Emmanuel Brunel D. Rohde Anna Korba OffRL 30 11 0 25 May 2023
A Rigorous Link between Deep Ensembles and (Variational) Bayesian Methods Veit Wild Sahra Ghalebikesabi Dino Sejdinovic Jeremias Knoblauch BDL UQCV 27 13 0 24 May 2023
Generalization Bounds for Neural Belief Propagation Decoders S. Adiga Xin Xiao Ravi Tandon Bane V. Vasic Tamal Bose BDL AI4CE 22 4 0 17 May 2023
Exactly Tight Information-Theoretic Generalization Error Bound for the Quadratic Gaussian Problem Ruida Zhou C. Tian Tie Liu 36 3 0 01 May 2023
Exponential Stochastic Inequality Peter Grünwald M. F. Pérez-Ortiz Zakaria Mhammedi 21 1 0 27 Apr 2023
Wasserstein PAC-Bayes Learning: Exploiting Optimisation Guarantees to Explain Generalisation Maxime Haddouche Benjamin Guedj 25 0 0 14 Apr 2023
The No Free Lunch Theorem, Kolmogorov Complexity, and the Role of Inductive Biases in Machine Learning Micah Goldblum Marc Finzi K. Rowan A. Wilson UQCV FedML 16 37 0 11 Apr 2023
PAC-Bayesian bounds for learning LTI-ss systems with input from empirical loss Deividas Eringis J. Leth Z. Tan R. Wisniewski M. Petreczky 11 3 0 29 Mar 2023
PAC-Bayes Bounds for High-Dimensional Multi-Index Models with Unknown Active Dimension Maximilian F. Steffen 30 1 0 23 Mar 2023
Bayes Complexity of Learners vs Overfitting Grzegorz Gluch R. Urbanke UQCV BDL 9 0 0 13 Mar 2023
Learning Hybrid Interpretable Models: Theory, Taxonomy, and Methods Julien Ferry Gabriel Laberge Ulrich Aivodji 26 5 0 08 Mar 2023
Bayes meets Bernstein at the Meta Level: an Analysis of Fast Rates in Meta-Learning with PAC-Bayes Charles Riou Pierre Alquier Badr-Eddine Chérief-Abdellatif 40 8 0 23 Feb 2023
PAC-Bayesian Generalization Bounds for Adversarial Generative Models S. Mbacke Florence Clerc Pascal Germain 24 8 0 17 Feb 2023
Tighter PAC-Bayes Bounds Through Coin-Betting Kyoungseok Jang Kwang-Sung Jun Ilja Kuzborskij Francesco Orabona 26 15 0 12 Feb 2023
A unified recipe for deriving (time-uniform) PAC-Bayes bounds Ben Chugg Hongjian Wang Aaditya Ramdas 24 24 0 07 Feb 2023