:: Library Catalog

Image de couverture de livre

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Zhou, Runlin, Chen, Chixiang, Chen, Elynn
Format:	Preprint
Publié:	2025
Sujets:	Machine Learning
Accès en ligne:	https://arxiv.org/abs/2510.05446
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Adaptive Prior Selection in Gaussian Process Bandits with Thompson Sampling
par: Sandberg, Jack, et autres
Publié: (2025)

Fast Online Learning with Gaussian Prior-Driven Hierarchical Unimodal Thompson Sampling
par: Zhao, Tianchi, et autres
Publié: (2026)

Dynamic Prior Thompson Sampling for Cold-Start Exploration in Recommender Systems
par: Zhao, Zhenyu, et autres
Publié: (2026)

Dual-Channel Tensor Neural Networks: Finite-Sample Theory and Conformal Structure Selection
par: Chen, Elynn, et autres
Publié: (2026)

Landscape of Policy Optimization for Finite Horizon MDPs with General State and Action
par: Chen, Xin, et autres
Publié: (2024)

No-Regret Thompson Sampling for Finite-Horizon Markov Decision Processes with Gaussian Processes
par: Bayrooti, Jasmine, et autres
Publié: (2025)

High-Dimensional Tensor Discriminant Analysis: Low-Rank Discriminant Structure, Representation Synergy, and Theoretical Guarantees
par: Chen, Elynn, et autres
Publié: (2025)

One-Step Bellman Alignment Enables Provably Efficient Transfer in Online RL
par: Chen, Elynn, et autres
Publié: (2026)

RL in Latent MDPs is Tractable: Online Guarantees via Off-Policy Evaluation
par: Kwon, Jeongyeol, et autres
Publié: (2024)

Addressing Finite-Horizon MDPs via Low-Rank Tensor Value Approximation
par: Rozada, Sergio, et autres
Publié: (2025)

PFN-TS: Thompson Sampling for Contextual Bandits via Prior-Data Fitted Networks
par: Tan, Yan Shuo, et autres
Publié: (2026)

Data-Driven Knowledge Transfer in Batch $Q^*$ Learning
par: Chen, Elynn, et autres
Publié: (2024)

Deep Transfer $Q$-Learning for Offline Non-Stationary Reinforcement Learning
par: Chai, Jinhang, et autres
Publié: (2025)

Transfer Learning for Contextual Joint Assortment-Pricing under Cross-Market Heterogeneity
par: Chen, Elynn, et autres
Publié: (2026)

Reinforcement Learning for Infinite-Horizon Average-Reward Linear MDPs via Approximation by Discounted-Reward MDPs
par: Hong, Kihyuk, et autres
Publié: (2024)

Transition Transfer $Q$-Learning for Composite Markov Decision Processes
par: Chai, Jinhang, et autres
Publié: (2025)

Amortising Inference and Meta-Learning Priors in Neural Networks
par: Rochussen, Tommy, et autres
Publié: (2026)

Aligning Latent Spaces with Flow Priors
par: Li, Yizhuo, et autres
Publié: (2025)

Thompson Sampling for Repeated Newsvendor
par: Chen, Li, et autres
Publié: (2025)

Optimal Variance-Dependent Regret Bounds for Infinite-Horizon MDPs
par: Zamir, Guy, et autres
Publié: (2026)

Language-Induced Priors for Domain Adaptation
par: Chen, Qiyuan, et autres
Publié: (2026)

Generalization Guarantees for Representation Learning via Data-Dependent Gaussian Mixture Priors
par: Sefidgaran, Milad, et autres
Publié: (2025)

Policy Gradient in Robust MDPs with Global Convergence Guarantee
par: Wang, Qiuhao, et autres
Publié: (2022)

Sample-Mean Anchored Thompson Sampling for Offline-to-Online Learning with Distribution Shift
par: Li, Bochao, et autres
Publié: (2026)

CAESAR: Enhancing Federated RL in Heterogeneous MDPs through Convergence-Aware Sampling with Screening
par: Mak, Hei Yi, et autres
Publié: (2024)

Reinforcement Learning for Control with Probabilistic Stability Guarantee: A Finite-Sample Approach
par: Han, Minghao, et autres
Publié: (2026)

Exploiting Causal Graph Priors with Posterior Sampling for Reinforcement Learning
par: Mutti, Mirco, et autres
Publié: (2023)

Tensor-Fused Multi-View Graph Contrastive Learning
par: Wu, Yujia, et autres
Publié: (2024)

Distilled Thompson Sampling: Practical and Efficient Thompson Sampling via Imitation Learning
par: Namkoong, Hongseok, et autres
Publié: (2020)

Regenerative Particle Thompson Sampling
par: Zhou, Zeyu, et autres
Publié: (2022)

Tensor-view Topological Graph Neural Network
par: Wen, Tao, et autres
Publié: (2024)

ALIGN: Aligned Delegation with Performance Guarantees for Multi-Agent LLM Reasoning
par: Zhu, Tong, et autres
Publié: (2026)

Online Posterior Sampling with a Diffusion Prior
par: Kveton, Branislav, et autres
Publié: (2024)

Low-Rank Plus Sparse Matrix Transfer Learning under Growing Representations and Ambient Dimensions
par: Chai, Jinhang, et autres
Publié: (2026)

A Finite Time Analysis of Thompson Sampling for Bayesian Optimization with Preferential Feedback
par: Lazzaro, Joseph, et autres
Publié: (2026)

Capacity-Aware Planning and Scheduling in Budget-Constrained Multi-Agent MDPs: A Meta-RL Approach
par: Vora, Manav, et autres
Publié: (2024)

Fast Non-Episodic Finite-Horizon RL with K-Step Lookahead Thresholding
par: Xu, Jiamin, et autres
Publié: (2026)

Solving robust MDPs as a sequence of static RL problems
par: Zouitine, Adil, et autres
Publié: (2024)

Where Not to Learn: Prior-Aligned Training with Subset-based Attribution Constraints for Reliable Decision-Making
par: Chen, Ruoyu, et autres
Publié: (2026)

Row-wise Fusion Regularization: An Interpretable Personalized Federated Learning Framework in Large-Scale Scenarios
par: Zhou, Runlin, et autres
Publié: (2025)