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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
User-friendly introduction to PAC-Bayes bounds Pierre Alquier FedML 193 207 0 21 Oct 2021
Perturbated Gradients Updating within Unit Space for Deep Learning Ching-Hsun Tseng Liu Cheng Shin-Jye Lee Xiaojun Zeng 113 5 0 01 Oct 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 116 31 0 21 Sep 2021
Kernel PCA with the Nyström method Fredrik Hallgren 46 3 0 12 Sep 2021
Multi-task Federated Edge Learning (MtFEEL) in Wireless Networks Sawan Singh Mahara M. Shruti B. Bharath Akash Murthy FedML 85 0 0 05 Aug 2021
On Margins and Derandomisation in PAC-Bayes Felix Biggs Benjamin Guedj 93 20 0 08 Jul 2021
Subgroup Generalization and Fairness of Graph Neural Networks Jiaqi Ma Junwei Deng Qiaozhu Mei 98 82 0 29 Jun 2021
Learning Stochastic Majority Votes by Minimizing a PAC-Bayes Generalization Bound Valentina Zantedeschi Paul Viallard Emilie Morvant Rémi Emonet Amaury Habrard Pascal Germain Benjamin Guedj FedML BDL 105 17 0 23 Jun 2021
Wide stochastic networks: Gaussian limit and PAC-Bayesian training Eugenio Clerico George Deligiannidis Arnaud Doucet 111 12 0 17 Jun 2021
Meta-Learning Reliable Priors in the Function Space Jonas Rothfuss Dominique Heyn Jinfan Chen Andreas Krause 84 28 0 06 Jun 2021
A unified PAC-Bayesian framework for machine unlearning via information risk minimization Sharu Theresa Jose Osvaldo Simeone MU 78 7 0 01 Jun 2021
PAC Bayesian Performance Guarantees for Deep (Stochastic) Networks in Medical Imaging Anthony Sicilia Xingchen Zhao Anastasia Sosnovskikh Seong Jae Hwang BDL UQCV 80 4 0 12 Apr 2021
Stopping Criterion for Active Learning Based on Error Stability Hideaki Ishibashi H. Hino 66 12 0 05 Apr 2021
PAC-Bayesian theory for stochastic LTI systems Deividas Eringis J. Leth Zheng-Hua Tan Rafal Wisniewski Alireza Fakhrizadeh Esfahani Mihaly Petreczky 107 9 0 23 Mar 2021
Tighter expected generalization error bounds via Wasserstein distance Borja Rodríguez Gálvez Germán Bassi Ragnar Thobaben Mikael Skoglund 79 46 0 22 Jan 2021
Bayesian inference in high-dimensional models Sayantan Banerjee I. Castillo S. Ghosal 120 23 0 12 Jan 2021
Minimum Excess Risk in Bayesian Learning Aolin Xu Maxim Raginsky 427 40 0 29 Dec 2020
Upper and Lower Bounds on the Performance of Kernel PCA Maxime Haddouche Benjamin Guedj John Shawe-Taylor 120 4 0 18 Dec 2020
Gibbs posterior concentration rates under sub-exponential type losses Nicholas Syring Ryan Martin 124 29 0 08 Dec 2020
Generalization bounds for deep learning Guillermo Valle Pérez A. Louis BDL 84 45 0 07 Dec 2020
A PAC-Bayesian Perspective on Structured Prediction with Implicit Loss Embeddings Théophile Cantelobre Benjamin Guedj Maria Perez-Ortiz John Shawe-Taylor 91 3 0 07 Dec 2020
Risk-Monotonicity in Statistical Learning Zakaria Mhammedi 144 8 0 28 Nov 2020
Generalized Posteriors in Approximate Bayesian Computation Sebastian M. Schmon Patrick W Cannon Jeremias Knoblauch 111 25 0 17 Nov 2020
A Quantitative Perspective on Values of Domain Knowledge for Machine Learning Jianyi Yang Shaolei Ren FAtt FaML 61 5 0 17 Nov 2020
Transfer Meta-Learning: Information-Theoretic Bounds and Information Meta-Risk Minimization Sharu Theresa Jose Osvaldo Simeone G. Durisi 118 17 0 04 Nov 2020
Robust Bayesian Inference for Discrete Outcomes with the Total Variation Distance Jeremias Knoblauch Lara Vomfell 72 7 0 26 Oct 2020
Fast-Rate Loss Bounds via Conditional Information Measures with Applications to Neural Networks Fredrik Hellström G. Durisi 99 2 0 22 Oct 2020
PAC $^m$ -Bayes: Narrowing the Empirical Risk Gap in the Misspecified Bayesian Regime Warren Morningstar Alexander A. Alemi Joshua V. Dillon 130 16 0 19 Oct 2020
Non-exponentially weighted aggregation: regret bounds for unbounded loss functions Pierre Alquier 105 19 0 07 Sep 2020
Tighter risk certificates for neural networks Maria Perez-Ortiz Omar Rivasplata John Shawe-Taylor Csaba Szepesvári UQCV 93 108 0 25 Jul 2020
Adaptive Task Sampling for Meta-Learning Chenghao Liu Zhihao Wang Doyen Sahoo Yuan Fang Kun Zhang Guosheng Lin 104 55 0 17 Jul 2020
PAC-Bayesian Bound for the Conditional Value at Risk Zakaria Mhammedi Benjamin Guedj Robert C. Williamson 78 21 0 26 Jun 2020
A Limitation of the PAC-Bayes Framework Roi Livni Shay Moran 97 25 0 24 Jun 2020
On the role of data in PAC-Bayes bounds Gintare Karolina Dziugaite Kyle Hsu W. Gharbieh Gabriel Arpino Daniel M. Roy 90 78 0 19 Jun 2020
PAC-Bayes unleashed: generalisation bounds with unbounded losses Maxime Haddouche Benjamin Guedj Omar Rivasplata John Shawe-Taylor 100 56 0 12 Jun 2020
Generalization Bounds via Information Density and Conditional Information Density Fredrik Hellström G. Durisi 132 67 0 16 May 2020
Practical calibration of the temperature parameter in Gibbs posteriors Lucie Perrotta 50 3 0 22 Apr 2020
Generalization Error Bounds via $m$ th Central Moments of the Information Density Fredrik Hellström G. Durisi 69 5 0 20 Apr 2020
Computing Bayes: Bayesian Computation from 1763 to the 21st Century G. Martin David T. Frazier Christian P. Robert 104 17 0 14 Apr 2020
Bayesian Deep Learning and a Probabilistic Perspective of Generalization A. Wilson Pavel Izmailov UQCV BDL OOD 181 658 0 20 Feb 2020
PACOH: Bayes-Optimal Meta-Learning with PAC-Guarantees Jonas Rothfuss Vincent Fortuin Martin Josifoski Andreas Krause UQCV 93 127 0 13 Feb 2020
Improved PAC-Bayesian Bounds for Linear Regression V. Shalaeva Alireza Fakhrizadeh Esfahani Pascal Germain Mihaly Petreczky 72 16 0 06 Dec 2019
Unifying Variational Inference and PAC-Bayes for Supervised Learning that Scales Sanjay Thakur H. V. Hoof Gunshi Gupta David Meger BDL 42 2 0 23 Oct 2019
PAC-Bayesian Contrastive Unsupervised Representation Learning Kento Nozawa Pascal Germain Benjamin Guedj SSL BDL 100 28 0 10 Oct 2019
Still no free lunches: the price to pay for tighter PAC-Bayes bounds Benjamin Guedj L. Pujol FedML 97 23 0 10 Oct 2019
Fast-rate PAC-Bayes Generalization Bounds via Shifted Rademacher Processes Jun Yang Shengyang Sun Daniel M. Roy 95 28 0 20 Aug 2019
Convergence Rates of Variational Inference in Sparse Deep Learning Badr-Eddine Chérief-Abdellatif BDL 125 39 0 09 Aug 2019
Chaining Meets Chain Rule: Multilevel Entropic Regularization and Training of Neural Nets Amir-Reza Asadi Emmanuel Abbe BDL AI4CE 85 13 0 26 Jun 2019
PAC-Bayes Un-Expected Bernstein Inequality Zakaria Mhammedi Peter Grünwald Benjamin Guedj 75 47 0 31 May 2019
Dichotomize and Generalize: PAC-Bayesian Binary Activated Deep Neural Networks Gaël Letarte Pascal Germain Benjamin Guedj Franccois Laviolette MQ AI4CE UQCV 93 54 0 24 May 2019