pac-bayesian analysis

Efficient Source-Free Time-Series Adaptation via Parameter Subspace Disentanglement ICLR 2025 Comparing Comparators in Generalization Bounds AISTATS 2024 Dual-Level Curriculum Meta-Learning for Noisy Few-Shot Learning Tasks AAAI 2024 Recursive PAC-Bayes: A Frequentist Approach to Sequential Prior Updates with No Information Loss NeurIPS 2024 Erratum: Risk Bounds for the Majority Vote: From a PAC-Bayesian Analysis to a Learning Algorithm JMLR 2023 Generalization in Graph Neural Networks: Improved PAC-Bayesian Bounds on Graph Diffusion AISTATS 2023 The Fine Print on Tempered Posteriors ACML 2023 PInKS: Preconditioned Commonsense Inference with Minimal Supervision AACL 2022 Subgroup Generalization and Fairness of Graph Neural Networks NeurIPS 2021 USCO-Solver: Solving Undetermined Stochastic Combinatorial Optimization Problems NeurIPS 2021 Normalized Flat Minima: Exploring Scale Invariant Definition of Flat Minima for Neural Networks Using PAC-Bayesian Analysis ICML 2020 Bayesian Counterfactual Risk Minimization ICML 2019 A PAC-Bayesian Analysis of Randomized Learning with Application to Stochastic Gradient Descent NeurIPS 2017 Risk Bounds for the Majority Vote: From a PAC-Bayesian Analysis to a Learning Algorithm JMLR 2015 PAC-Bayesian Analysis of Contextual Bandits NeurIPS 2011 PAC-Bayesian Analysis of Co-clustering and Beyond JMLR 2010 Transfer Learning using Kolmogorov Complexity: Basic Theory and Empirical Evaluations NeurIPS 2007