Bayesian Learning

ADEPT: Hierarchical Bayes Approach to Personalized Federated Unsupervised Learning AISTATS 2025 An Asymptotically Optimal Coordinate Descent Algorithm for Learning Bayesian Networks from Gaussian Models JMLR 2025 A Safe Bayesian Learning Algorithm for Constrained MDPs with Bounded Constraint Violation AISTATS 2025 Bayesian Low-Rank Learning (Bella): A Practical Approach to Bayesian Neural Networks AAAI 2025 Bayes Meets Bernstein at the Meta Level: an Analysis of Fast Rates in Meta-Learning with PAC-Bayes JMLR 2025 Cache-Efficient Posterior Sampling for Reinforcement Learning with LLM-Derived Priors Across Discrete and Continuous Domains EMNLP 2025 Combining Climate Models using Bayesian Regression Trees and Random Paths JMLR 2025 Cross-Framework Generalizable Discourse Relation Classification Through Cognitive Dimensions NAACL 2025 Decomposed Quadratization: Efficient QUBO Formulation for Learning Bayesian Network AAAI 2025 Hypernetwork Approach to Bayesian MAML (Student Abstract) AAAI 2025 pFedGPT: Hierarchically Optimizing LoRA Aggregation Weights for Personalized Federated GPT Models EMNLP 2025 Proxy-informed Bayesian transfer learning with unknown sources UAI 2025 Sketching in High-Dimensional Regression With Big Data Using Gaussian Scale Mixture Priors JMLR 2025 Statistical Guarantees for Lifelong Reinforcement Learning using PAC-Bayes Theory AISTATS 2025 Stochastic Weight Sharing for Bayesian Neural Networks AISTATS 2025 A Bayesian Learning Algorithm for Unknown Zero-sum Stochastic Games with an Arbitrary Opponent AISTATS 2024 A flexible empirical Bayes approach to multiple linear regression and connections with penalized regression JMLR 2024 Bayesian Domain Adaptation with Gaussian Mixture Domain-Indexing NeurIPS 2024 Bayesian Exploration of Pre-trained Models for Low-shot Image Classification CVPR 2024 Bayesian Online Learning for Consensus Prediction AISTATS 2024 Bayes-optimal learning of an extensive-width neural network from quadratically many samples NeurIPS 2024 Beyond Single Stationary Policies: Meta-Task Players as Naturally Superior Collaborators NeurIPS 2024 Calibrated One Round Federated Learning with Bayesian Inference in the Predictive Space AAAI 2024 Choosing the Number of Topics in LDA Models – A Monte Carlo Comparison of Selection Criteria JMLR 2024 Computation-Aware Gaussian Processes: Model Selection And Linear-Time Inference NeurIPS 2024