{"total":52,"rows":[{"id":"2110.11216","title":"User-friendly introduction to PAC-Bayes bounds","created":"2021-10-21","cited_by_count":239,"area":null},{"id":"2211.13609","title":"PAC-Bayes Compression Bounds So Tight That They Can Explain Generalization","created":"2022-11-24","cited_by_count":76,"area":null},{"id":"2202.11678","title":"Bayesian Model Selection, the Marginal Likelihood, and Generalization","created":"2022-02-23","cited_by_count":57,"area":null},{"id":"2203.06020","title":"Enhancing Adversarial Training with Second-Order Statistics of Weights","created":"2022-03-11","cited_by_count":42,"area":null},{"id":"2102.06589","title":"Generalization Bounds for Meta-Learning via PAC-Bayes and Uniform Stability","created":"2021-02-12","cited_by_count":30,"area":null},{"id":"2302.03421","title":"A unified recipe for deriving (time-uniform) PAC-Bayes bounds","created":"2023-02-07","cited_by_count":25,"area":null},{"id":"2106.03542","title":"How Tight Can PAC-Bayes be in the Small Data Regime?","created":"2021-06-07","cited_by_count":24,"area":null},{"id":"2210.00928","title":"PAC-Bayes Generalisation Bounds for Heavy-Tailed Losses through Supermartingales","created":"2022-10-03","cited_by_count":24,"area":null},{"id":"2206.00024","title":"Online PAC-Bayes Learning","created":"2022-05-31","cited_by_count":22,"area":null},{"id":"2312.11875","title":"Sparse is Enough in Fine-tuning Pre-trained Large Language Models","created":"2023-12-19","cited_by_count":21,"area":null},{"id":"2306.12214","title":"More PAC-Bayes bounds: From bounded losses, to losses with general tail behaviors, to anytime validity","created":"2023-06-21","cited_by_count":17,"area":null},{"id":"2106.12535","title":"Learning Stochastic Majority Votes by Minimizing a PAC-Bayes Generalization Bound","created":"2021-06-23","cited_by_count":16,"area":null},{"id":"2310.04935","title":"Statistical Guarantees for Variational Autoencoders using PAC-Bayesian Theory","created":"2023-10-07","cited_by_count":16,"area":null},{"id":"2105.01747","title":"Information Complexity and Generalization Bounds","created":"2021-05-04","cited_by_count":14,"area":null},{"id":"2106.13624","title":"Chebyshev-Cantelli PAC-Bayes-Bennett Inequality for the Weighted Majority Vote","created":"2021-06-25","cited_by_count":13,"area":null},{"id":"2102.02016","title":"Information-Theoretic Bounds on the Moments of the Generalization Error of Learning Algorithms","created":"2021-02-03","cited_by_count":12,"area":null},{"id":"2102.03748","title":"PAC-Bayes Bounds for Meta-learning with Data-Dependent Prior","created":"2021-02-07","cited_by_count":11,"area":null},{"id":"2206.00706","title":"Split-kl and PAC-Bayes-split-kl Inequalities for Ternary Random Variables","created":"2022-06-01","cited_by_count":11,"area":null},{"id":"2106.09798","title":"Wide stochastic networks: Gaussian limit and PAC-Bayesian training","created":"2021-06-17","cited_by_count":10,"area":null},{"id":"2303.05369","title":"Data-dependent Generalization Bounds via Variable-Size Compressibility","created":"2023-03-09","cited_by_count":9,"area":null},{"id":"2401.01148","title":"PAC-Bayes-Chernoff bounds for unbounded losses","created":"2024-01-02","cited_by_count":9,"area":null},{"id":"2305.04979","title":"FedHB: Hierarchical Bayesian Federated Learning","created":"2023-05-08","cited_by_count":8,"area":null},{"id":"2110.11886","title":"Conditionally Gaussian PAC-Bayes","created":"2021-10-22","cited_by_count":7,"area":null},{"id":"2206.04607","title":"On Margins and Generalisation for Voting Classifiers","created":"2022-06-09","cited_by_count":7,"area":null},{"id":"2211.16110","title":"PAC-Bayes Bounds for Bandit Problems: A Survey and Experimental Comparison","created":"2022-11-29","cited_by_count":7,"area":null},{"id":"2201.09209","title":"Weight Expansion: A New Perspective on Dropout and Generalization","created":"2022-01-23","cited_by_count":6,"area":null},{"id":"2305.19243","title":"Improving Generalization of Complex Models under Unbounded Loss Using PAC-Bayes Bounds","created":"2023-05-30","cited_by_count":6,"area":null},{"id":"2106.13703","title":"Task-Driven Detection of Distribution Shifts with Statistical Guarantees for Robot Learning","created":"2021-06-25","cited_by_count":4,"area":null},{"id":"2210.11113","title":"PAC-Bayesian Learning of Optimization Algorithms","created":"2022-10-20","cited_by_count":4,"area":null},{"id":"2405.14681","title":"Recursive PAC-Bayes: A Frequentist Approach to Sequential Prior Updates with No Information Loss","created":"2024-05-23","cited_by_count":4,"area":null},{"id":"2109.14422","title":"Multi-class Probabilistic Bounds for Self-learning","created":"2021-09-29","cited_by_count":3,"area":null},{"id":"2206.05454","title":"A General framework for PAC-Bayes Bounds for Meta-Learning","created":"2022-06-11","cited_by_count":3,"area":null},{"id":"2410.13577","title":"Generalization Bounds via Meta-Learned Model Representations: PAC-Bayes and Sample Compression Hypernetworks","created":"2024-10-17","cited_by_count":3,"area":null},{"id":"2510.25569","title":"A Framework for Bounding Deterministic Risk with PAC-Bayes: Applications to Majority Votes","created":"2025-10-29","cited_by_count":3,"area":null},{"id":"2201.11162","title":"Self-Certifying Classification by Linearized Deep Assignment","created":"2022-01-26","cited_by_count":2,"area":null},{"id":"2405.00442","title":"Geometric Insights into Focal Loss: Reducing Curvature for Enhanced Model Calibration","created":"2024-05-01","cited_by_count":2,"area":null},{"id":"2502.15540","title":"Generalization Guarantees for Representation Learning via Data-Dependent Gaussian Mixture Priors","created":"2025-02-21","cited_by_count":2,"area":null},{"id":"2509.25979","title":"Reconcile Certified Robustness and Accuracy for DNN-based Smoothed Majority Vote Classifier","created":"2025-09-30","cited_by_count":2,"area":null},{"id":"2111.08761","title":"Stronger Generalization Guarantees for Robot Learning by Combining Generative Models and Real-World Data","created":"2021-11-16","cited_by_count":1,"area":null},{"id":"2202.01958","title":"Demystify Optimization and Generalization of Over-parameterized PAC-Bayesian Learning","created":"2022-02-04","cited_by_count":1,"area":null},{"id":"2301.00736","title":"Mixed moving average field guided learning for spatio-temporal data","created":"2023-01-02","cited_by_count":1,"area":null},{"id":"2310.12882","title":"Sequential Gibbs Posteriors with Applications to Principal Component Analysis","created":"2023-10-19","cited_by_count":1,"area":null},{"id":"2310.20053","title":"Estimating optimal PAC-Bayes bounds with Hamiltonian Monte Carlo","created":"2023-10-30","cited_by_count":1,"area":null},{"id":"2410.07704","title":"A Generalization Result for Convergence in Learning-to-Optimize","created":"2024-10-10","cited_by_count":1,"area":null},{"id":"2411.06276","title":"Multi-View Majority Vote Learning Algorithms: Direct Minimization of PAC-Bayesian Bounds","created":"2024-11-09","cited_by_count":1,"area":null},{"id":"2504.18455","title":"Multiview Representation Learning via Distributed Joint Latent Space Structuring","created":"2025-04-25","cited_by_count":1,"area":null},{"id":"2510.07935","title":"Some theoretical improvements on the tightness of PAC-Bayes risk certificates for neural networks","created":"2025-10-09","cited_by_count":1,"area":null},{"id":"2306.09702","title":"A Hierarchical Bayesian Model for Deep Few-Shot Meta Learning","created":"2023-06-16","cited_by_count":0,"area":null},{"id":"2310.02885","title":"Something for (almost) nothing: Improving deep ensemble calibration using unlabeled data","created":"2023-10-04","cited_by_count":0,"area":null},{"id":"2406.05469","title":"On Uniform, Bayesian, and PAC-Bayesian Deep Ensembles","created":"2024-06-08","cited_by_count":0,"area":null},{"id":"2603.01264","title":"S2O: Enhancing Adversarial Training with Second-Order Statistics of Weights","created":"2026-03-01","cited_by_count":0,"area":null},{"id":"2609.16803","title":"On the disintegration of the stochastic majority vote: From PAC-Bayesian bounds to a self-bounding algorithm","created":"2026-09-15","cited_by_count":0,"area":null}],"next_cursor":null}