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pac-bayesian theory

34 papers

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Also known as

PAC-BAYESIAN PAC-BAYES

Co-occurring keywords

generalization bound (652) pac-bayesian bound (40) generalization error (285) neural network (6616) generative model (2892) concentration inequality (81) learning theory (519) wasserstein distance (417) statistical guarantee (33) stochastic gradient langevin dynamics (49)

Papers

Learning-to-Optimize with PAC-Bayesian Guarantees: Theoretical Considerations and Practical Implementation JMLR 2025
Meta-Learning via PAC-Bayesian with Data-Dependent Prior: Generalization Bounds from Local Entropy IJCAI 2024
Non-vacuous Generalization Bounds for Adversarial Risk in Stochastic Neural Networks AISTATS 2024
Information-Theoretic Generalization Bounds for Transductive Learning and its Applications JMLR 2024
Uniform Generalization Bounds on Data-Dependent Hypothesis Sets via PAC-Bayesian Theory on Random Sets JMLR 2024
PAC-Bayesian Generalization Bounds for Adversarial Generative Models ICML 2023
Optimization and Bayes: A Trade-off for Overparameterized Neural Networks NIPS 2023
Statistical Guarantees for Variational Autoencoders using PAC-Bayesian Theory NIPS 2023
Generalization in Graph Neural Networks: Improved PAC-Bayesian Bounds on Graph Diffusion AISTATS 2023
Failure Prediction with Statistical Guarantees for Vision-Based Robot Control RSS 2022
On PAC-Bayesian reconstruction guarantees for VAEs AISTATS 2022
Non-Vacuous Generalisation Bounds for Shallow Neural Networks ICML 2022
PAC-Bayesian Bounds on Rate-Efficient Classifiers ICML 2022
Analyzing Lottery Ticket Hypothesis from PAC-Bayesian Theory Perspective NIPS 2022
An Optimization-centric View on Bayes' Rule: Reviewing and Generalizing Variational Inference JMLR 2022
Learning Partially Known Stochastic Dynamics with Empirical PAC Bayes AISTATS 2021
Bridging the Gap Between Practice and PAC-Bayes Theory in Few-Shot Meta-Learning NIPS 2021
Task-Driven Out-of-Distribution Detection with Statistical Guarantees for Robot Learning CORL 2021
PAC-Bayesian Bound for the Conditional Value at Risk NIPS 2020
PAC-Bayesian Contrastive Unsupervised Representation Learning UAI 2020
Normalized Flat Minima: Exploring Scale Invariant Definition of Flat Minima for Neural Networks Using PAC-Bayesian Analysis ICML 2020
Improving the Robustness of Wasserstein Embedding by Adversarial PAC-Bayesian Learning AAAI 2020
Stopping criterion for active learning based on deterministic generalization bounds AISTATS 2020
Pseudo-Bayesian Learning with Kernel Fourier Transform as Prior AISTATS 2019
PAC-Bayes under potentially heavy tails NIPS 2019