{"total":76,"rows":[{"id":"2112.10510","title":"Transformers Can Do Bayesian Inference","created":"2021-12-20","cited_by_count":360,"area":null},{"id":"2110.11216","title":"User-friendly introduction to PAC-Bayes bounds","created":"2021-10-21","cited_by_count":239,"area":null},{"id":"2107.02729","title":"AdaRL: What, Where, and How to Adapt in Transfer Reinforcement Learning","created":"2021-07-06","cited_by_count":48,"area":null},{"id":"2109.14595","title":"Generalization Bounds For Meta-Learning: An Information-Theoretic Analysis","created":"2021-09-29","cited_by_count":45,"area":null},{"id":"2105.02221","title":"How Fine-Tuning Allows for Effective Meta-Learning","created":"2021-05-05","cited_by_count":41,"area":null},{"id":"2210.10837","title":"On Learning Fairness and Accuracy on Multiple Subgroups","created":"2022-10-19","cited_by_count":32,"area":null},{"id":"2102.04002","title":"Meta Discovery: Learning to Discover Novel Classes given Very Limited Data","created":"2021-02-08","cited_by_count":31,"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":"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":"2106.03195","title":"Meta-Learning Reliable Priors in the Function Space","created":"2021-06-06","cited_by_count":23,"area":null},{"id":"2105.14099","title":"Bridging the Gap Between Practice and PAC-Bayes Theory in Few-Shot Meta-Learning","created":"2021-05-28","cited_by_count":21,"area":null},{"id":"2306.05515","title":"PeFLL: Personalized Federated Learning by Learning to Learn","created":"2023-06-08","cited_by_count":21,"area":null},{"id":"2207.00614","title":"Integral Probability Metrics PAC-Bayes Bounds","created":"2022-07-01","cited_by_count":19,"area":null},{"id":"2207.06046","title":"Learning Deep Time-index Models for Time Series Forecasting","created":"2022-07-13","cited_by_count":18,"area":null},{"id":"2210.03067","title":"Few-Shot Calibration of Set Predictors via Meta-Learned Cross-Validation-Based Conformal Prediction","created":"2022-10-06","cited_by_count":17,"area":null},{"id":"2107.05320","title":"Metalearning Linear Bandits by Prior Update","created":"2021-07-12","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":"2210.00762","title":"Meta-Learning Priors for Safe Bayesian Optimization","created":"2022-10-03","cited_by_count":14,"area":null},{"id":"2203.03059","title":"Is Bayesian Model-Agnostic Meta Learning Better than Model-Agnostic Meta Learning, Provably?","created":"2022-03-06","cited_by_count":13,"area":null},{"id":"2302.08942","title":"PAC-Bayesian Generalization Bounds for Adversarial Generative Models","created":"2023-02-17","cited_by_count":13,"area":null},{"id":"2306.04375","title":"Learning via Wasserstein-Based High Probability Generalisation Bounds","created":"2023-06-07","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":"2206.13482","title":"Understanding Benign Overfitting in Gradient-Based Meta Learning","created":"2022-06-27","cited_by_count":11,"area":null},{"id":"2210.06511","title":"Evaluated CMI Bounds for Meta Learning: Tightness and Expressiveness","created":"2022-10-12","cited_by_count":11,"area":null},{"id":"2211.07206","title":"Scalable PAC-Bayesian Meta-Learning via the PAC-Optimal Hyper-Posterior: From Theory to Practice","created":"2022-11-14","cited_by_count":11,"area":null},{"id":"2312.13978","title":"Metalearning with Very Few Samples Per Task","created":"2023-12-21","cited_by_count":11,"area":null},{"id":"2402.04054","title":"More Flexible PAC-Bayesian Meta-Learning by Learning Learning Algorithms","created":"2024-02-06","cited_by_count":11,"area":null},{"id":"2101.08390","title":"An Information-Theoretic Analysis of the Impact of Task Similarity on Meta-Learning","created":"2021-01-21","cited_by_count":10,"area":null},{"id":"2106.00252","title":"Information-Theoretic Analysis of Epistemic Uncertainty in Bayesian Meta-learning","created":"2021-06-01","cited_by_count":10,"area":null},{"id":"2412.13573","title":"Seeking Consistent Flat Minima for Better Domain Generalization via Refining Loss Landscapes","created":"2024-12-18","cited_by_count":10,"area":null},{"id":"2107.02378","title":"Learning an Explicit Hyperparameter Prediction Function Conditioned on Tasks","created":"2021-07-06","cited_by_count":9,"area":null},{"id":"2206.09136","title":"Provable Generalization of Overparameterized Meta-learning Trained with SGD","created":"2022-06-18","cited_by_count":9,"area":null},{"id":"2102.07358","title":"Weak Adaptation Learning -- Addressing Cross-domain Data Insufficiency with Weak Annotator","created":"2021-02-15","cited_by_count":8,"area":null},{"id":"2302.11709","title":"Bayes meets Bernstein at the Meta Level: an Analysis of Fast Rates in Meta-Learning with PAC-Bayes","created":"2023-02-23","cited_by_count":8,"area":null},{"id":"2109.11792","title":"Regularization Guarantees Generalization in Bayesian Reinforcement Learning through Algorithmic Stability","created":"2021-09-24","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":"2411.00401","title":"Statistical Guarantees for Lifelong Reinforcement Learning using PAC-Bayes Theory","created":"2024-11-01","cited_by_count":7,"area":"deeprl"},{"id":"2102.02504","title":"Meta-strategy for Learning Tuning Parameters with Guarantees","created":"2021-02-04","cited_by_count":6,"area":null},{"id":"2103.03901","title":"Fast On-Device Adaptation for Spiking Neural Networks via Online-Within-Online Meta-Learning","created":"2021-02-21","cited_by_count":6,"area":null},{"id":"2206.10716","title":"Meta Reinforcement Learning with Finite Training Tasks -- a Density Estimation Approach","created":"2022-06-21","cited_by_count":6,"area":null},{"id":"2210.06143","title":"On the Importance of Gradient Norm in PAC-Bayesian Bounds","created":"2022-10-12","cited_by_count":6,"area":null},{"id":"2311.07558","title":"Data-Efficient Task Generalization via Probabilistic Model-based Meta Reinforcement Learning","created":"2023-11-13","cited_by_count":6,"area":null},{"id":"2210.02617","title":"Generalization Properties of Retrieval-based Models","created":"2022-10-06","cited_by_count":5,"area":null},{"id":"2210.13319","title":"MARS: Meta-Learning as Score Matching in the Function Space","created":"2022-10-24","cited_by_count":5,"area":null},{"id":"2401.08351","title":"Personalized Federated Learning of Probabilistic Models: A PAC-Bayesian Approach","created":"2024-01-16","cited_by_count":5,"area":null},{"id":"2404.13831","title":"Data-Driven Performance Guarantees for Classical and Learned Optimizers","created":"2024-04-22","cited_by_count":5,"area":null},{"id":"2501.19067","title":"From Low Intrinsic Dimensionality to Non-Vacuous Generalization Bounds in Deep Multi-Task Learning","created":"2025-01-31","cited_by_count":5,"area":null},{"id":"2203.03303","title":"PAC-Bayesian Lifelong Learning For Multi-Armed Bandits","created":"2022-03-07","cited_by_count":4,"area":null},{"id":"2404.00688","title":"Meta Learning in Bandits within Shared Affine Subspaces","created":"2024-03-31","cited_by_count":4,"area":null},{"id":"2111.03628","title":"Exploiting a Zoo of Checkpoints for Unseen Tasks","created":"2021-11-05","cited_by_count":3,"area":null},{"id":"2203.17089","title":"Quantum-Aided Meta-Learning for Bayesian Binary Neural Networks via Born Machines","created":"2022-03-31","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":"2304.07048","title":"Wasserstein PAC-Bayes Learning: Exploiting Optimisation Guarantees to Explain Generalisation","created":"2023-04-14","cited_by_count":3,"area":null},{"id":"2406.09370","title":"Data-dependent and Oracle Bounds on Forgetting in Continual Learning","created":"2024-06-13","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":"2604.19312","title":"On the Conditioning Consistency Gap in Conditional Neural Processes","created":"2026-04-21","cited_by_count":3,"area":null},{"id":"2108.00785","title":"Bayesian Active Meta-Learning for Few Pilot Demodulation and Equalization","created":"2021-08-02","cited_by_count":2,"area":null},{"id":"2304.14332","title":"On the Generalization Error of Meta Learning for the Gibbs Algorithm","created":"2023-04-27","cited_by_count":2,"area":null},{"id":"2310.11203","title":"Federated Learning with Nonvacuous Generalisation Bounds","created":"2023-10-17","cited_by_count":2,"area":null},{"id":"2402.05101","title":"Tighter Generalisation Bounds via Interpolation","created":"2024-02-07","cited_by_count":2,"area":null},{"id":"2408.09703","title":"Partial-Multivariate Model for Forecasting","created":"2024-08-19","cited_by_count":2,"area":null},{"id":"2505.15496","title":"Fast Rate Bounds for Multi-Task and Meta-Learning with Different Sample Sizes","created":"2025-05-21","cited_by_count":2,"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":"2203.15972","title":"Higher-Order Generalization Bounds: Learning Deep Probabilistic Programs via PAC-Bayes Objectives","created":"2022-03-30","cited_by_count":1,"area":null},{"id":"2403.03535","title":"Task Attribute Distance for Few-Shot Learning: Theoretical Analysis and Applications","created":"2024-03-06","cited_by_count":1,"area":null},{"id":"2410.10230","title":"Learning via Surrogate PAC-Bayes","created":"2024-10-14","cited_by_count":1,"area":null},{"id":"2504.20310","title":"A Cryptographic Perspective on Mitigation vs. Detection in Machine Learning","created":"2025-04-28","cited_by_count":1,"area":null},{"id":"2106.10711","title":"Transfer Bayesian Meta-learning via Weighted Free Energy Minimization","created":"2021-06-20","cited_by_count":0,"area":null},{"id":"2207.00751","title":"Informed Learning by Wide Neural Networks: Convergence, Generalization and Sampling Complexity","created":"2022-07-02","cited_by_count":0,"area":null},{"id":"2207.06917","title":"Online Bayesian Meta-Learning for Cognitive Tracking Radar","created":"2022-07-07","cited_by_count":0,"area":null},{"id":"2210.02796","title":"Hypernetwork approach to Bayesian MAML","created":"2022-10-06","cited_by_count":0,"area":null},{"id":"2306.08460","title":"Improving Generalization in Meta-Learning via Meta-Gradient Augmentation","created":"2023-06-14","cited_by_count":0,"area":null},{"id":"2505.15579","title":"Federated Learning with Unlabeled Clients: Personalization Can Happen in Low Dimensions","created":"2025-05-21","cited_by_count":0,"area":null},{"id":"2509.17301","title":"On Quantification of Borrowing of Information in Hierarchical Bayesian Models","created":"2025-09-22","cited_by_count":0,"area":null},{"id":"2510.23448","title":"An Information-Theoretic Analysis of OOD Generalization in Meta-Reinforcement Learning","created":"2025-10-27","cited_by_count":0,"area":"deeprl"},{"id":"2606.02008","title":"Provable Data Scaling Law for Meta Learning via Complexity Minimization","created":"2026-06-01","cited_by_count":0,"area":null}],"next_cursor":null}