Meta-Learning by Adjusting Priors Based on Extended PAC-Bayes Theory

3 November 2017

Papers citing "Meta-Learning by Adjusting Priors Based on Extended PAC-Bayes Theory"

50 / 100 papers shown

Title
A Cryptographic Perspective on Mitigation vs. Detection in Machine Learning Greg Gluch Shafi Goldwasser AAML 37 0 0 28 Apr 2025
PeFLL: Personalized Federated Learning by Learning to Learn Jonathan Scott Hossein Zakerinia Christoph H. Lampert FedML 92 7 0 17 Jan 2025
Seeking Consistent Flat Minima for Better Domain Generalization via Refining Loss Landscapes Aodi Li Liansheng Zhuang Xiao Long Minghong Yao Shafei Wang 186 0 0 18 Dec 2024
Learning via Surrogate PAC-Bayes Antoine Picard-Weibel Roman Moscoviz Benjamin Guedj 23 0 0 14 Oct 2024
Partial-Multivariate Model for Forecasting Jaehoon Lee Hankook Lee Sungik Choi Sungjun Cho Moontae Lee AI4TS 44 0 0 19 Aug 2024
Meta Learning in Bandits within Shared Affine Subspaces Steven Bilaj Sofien Dhouib S. Maghsudi 39 2 0 31 Mar 2024
Task Attribute Distance for Few-Shot Learning: Theoretical Analysis and Applications Minyang Hu Hong Chang Zong Guo Bingpeng Ma Shiguang Shan Xilin Chen VLM 29 1 0 06 Mar 2024
Tighter Generalisation Bounds via Interpolation Paul Viallard Maxime Haddouche Umut Simsekli Benjamin Guedj 13 3 0 07 Feb 2024
More Flexible PAC-Bayesian Meta-Learning by Learning Learning Algorithms Hossein Zakerinia Amin Behjati Christoph H. Lampert FedML 24 4 0 06 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
Metalearning with Very Few Samples Per Task Maryam Aliakbarpour Konstantina Bairaktari Gavin Brown Adam D. Smith Nathan Srebro Jonathan Ullman VLM 29 2 0 21 Dec 2023
Data-Efficient Task Generalization via Probabilistic Model-based Meta Reinforcement Learning Arjun Bhardwaj Jonas Rothfuss Bhavya Sukhija Yarden As Marco Hutter Stelian Coros Andreas Krause 24 5 0 13 Nov 2023
Federated Learning with Nonvacuous Generalisation Bounds Pierre Jobic Maxime Haddouche Benjamin Guedj FedML 30 3 0 17 Oct 2023
Statistical Guarantees for Variational Autoencoders using PAC-Bayesian Theory S. Mbacke Florence Clerc Pascal Germain DRL 22 10 0 07 Oct 2023
Improving Generalization in Meta-Learning via Meta-Gradient Augmentation Ren Wang Haoliang Sun Qi Wei Xiushan Nie Yuling Ma Yilong Yin 18 0 0 14 Jun 2023
Learning via Wasserstein-Based High Probability Generalisation Bounds Paul Viallard Maxime Haddouche Umut Simsekli Benjamin Guedj 30 12 0 07 Jun 2023
On the Generalization Error of Meta Learning for the Gibbs Algorithm Yuheng Bu Harsha Vardhan Tetali Gholamali Aminian Miguel R. D. Rodrigues G. Wornell AI4CE 27 3 0 27 Apr 2023
Wasserstein PAC-Bayes Learning: Exploiting Optimisation Guarantees to Explain Generalisation Maxime Haddouche Benjamin Guedj 25 0 0 14 Apr 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 27 8 0 17 Feb 2023
PAC-Bayes Bounds for Bandit Problems: A Survey and Experimental Comparison H. Flynn David Reeb M. Kandemir Jan Peters OffRL 16 7 0 29 Nov 2022
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
MARS: Meta-Learning as Score Matching in the Function Space Krunoslav Lehman Pavasovic Jonas Rothfuss Andreas Krause BDL 30 4 0 24 Oct 2022
On Learning Fairness and Accuracy on Multiple Subgroups Changjian Shui Gezheng Xu Qi Chen Jiaqi Li Charles X. Ling Tal Arbel Boyu Wang Christian Gagné 44 37 0 19 Oct 2022
Evaluated CMI Bounds for Meta Learning: Tightness and Expressiveness Fredrik Hellström G. Durisi 21 13 0 12 Oct 2022
On the Importance of Gradient Norm in PAC-Bayesian Bounds Itai Gat Yossi Adi A. Schwing Tamir Hazan BDL 34 6 0 12 Oct 2022
Few-Shot Calibration of Set Predictors via Meta-Learned Cross-Validation-Based Conformal Prediction Sangwoo Park K. Cohen Osvaldo Simeone 20 13 0 06 Oct 2022
Hypernetwork approach to Bayesian MAML Piotr Borycki Piotr Kubacki Marcin Przewiȩźlikowski Tomasz Ku'smierczyk Jacek Tabor P. Spurek BDL 11 2 0 06 Oct 2022
Generalization Properties of Retrieval-based Models Soumya Basu A. S. Rawat Manzil Zaheer 29 6 0 06 Oct 2022
Meta-Learning Priors for Safe Bayesian Optimization Jonas Rothfuss Christopher Koenig Alisa Rupenyan Andreas Krause 33 29 0 03 Oct 2022
Learning Deep Time-index Models for Time Series Forecasting Gerald Woo Chenghao Liu Doyen Sahoo Akshat Kumar S. Hoi AI4TS AI4CE 34 26 0 13 Jul 2022
Online Bayesian Meta-Learning for Cognitive Tracking Radar C. Thornton R. M. Buehrer A. Martone 21 5 0 07 Jul 2022
Informed Learning by Wide Neural Networks: Convergence, Generalization and Sampling Complexity Jianyi Yang Shaolei Ren 24 3 0 02 Jul 2022
Integral Probability Metrics PAC-Bayes Bounds Ron Amit Baruch Epstein Shay Moran Ron Meir 24 18 0 01 Jul 2022
Understanding Benign Overfitting in Gradient-Based Meta Learning Lisha Chen Songtao Lu Tianyi Chen MLT 25 14 0 27 Jun 2022
Meta Reinforcement Learning with Finite Training Tasks -- a Density Estimation Approach Zohar Rimon Aviv Tamar Gilad Adler OOD OffRL 31 8 0 21 Jun 2022
Provable Generalization of Overparameterized Meta-learning Trained with SGD Yu Huang Yingbin Liang Longbo Huang MLT 26 8 0 18 Jun 2022
A General framework for PAC-Bayes Bounds for Meta-Learning A. Rezazadeh AI4CE 21 4 0 11 Jun 2022
Quantum-Aided Meta-Learning for Bayesian Binary Neural Networks via Born Machines I. Nikoloska Osvaldo Simeone AI4CE 11 3 0 31 Mar 2022
Higher-Order Generalization Bounds: Learning Deep Probabilistic Programs via PAC-Bayes Objectives J. Warrell M. Gerstein GP 14 1 0 30 Mar 2022
PAC-Bayesian Lifelong Learning For Multi-Armed Bandits H. Flynn David Reeb M. Kandemir Jan Peters 31 7 0 07 Mar 2022
Is Bayesian Model-Agnostic Meta Learning Better than Model-Agnostic Meta Learning, Provably? Lisha Chen Tianyi BDL 24 16 0 06 Mar 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
Transformers Can Do Bayesian Inference Samuel G. Müller Noah Hollmann Sebastian Pineda Arango Josif Grabocka Frank Hutter BDL UQCV 19 140 0 20 Dec 2021
Exploiting a Zoo of Checkpoints for Unseen Tasks Jiaji Huang Qiang Qiu Kenneth Ward Church 19 4 0 05 Nov 2021
User-friendly introduction to PAC-Bayes bounds Pierre Alquier FedML 60 196 0 21 Oct 2021
Generalization Bounds For Meta-Learning: An Information-Theoretic Analysis Qi Chen Changjian Shui M. Marchand 40 43 0 29 Sep 2021
Regularization Guarantees Generalization in Bayesian Reinforcement Learning through Algorithmic Stability Aviv Tamar Daniel Soudry E. Zisselman OOD OffRL 13 7 0 24 Sep 2021
Bayesian Active Meta-Learning for Few Pilot Demodulation and Equalization K. Cohen Sangwoo Park Osvaldo Simeone S. Shamai 23 12 0 02 Aug 2021
Metalearning Linear Bandits by Prior Update Amit Peleg Naama Pearl Ron Meir 32 18 0 12 Jul 2021