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thompson sampling

237 papers

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TS

Co-occurring keywords

regret bound (1926) multi-armed bandit (1098) bayesian optimization (624) online learning (1777) contextual bandit (381) bayesian inference (1907) upper confidence bound (197) bayesian regret (33) reinforcement learning (4352) posterior distribution (259)

Papers

Large Language Model-Enhanced Multi-Armed Bandits ACL 2026
Mango: Multi-Agent Web Navigation via Global-View Optimization ACL 2026
Sparse Nonparametric Contextual Bandits ALT 2026
MetaGameBO: Hierarchical Game-Theoretic Driven Robust Meta-Learning for Bayesian Optimization AAAI 2026
Learning to Instruct: Fine-Tuning a Task-Aware Instruction Optimizer for Black-Box LLMs EMNLP 2025
Anytime Multi-Agent Path Finding with an Adaptive Delay-Based Heuristic AAAI 2025
Multi-Objective Neural Bandits with Random Scalarization IJCAI 2025
Bandit-Based Prompt Design Strategy Selection Improves Prompt Optimizers ACL 2025
Context in Public Health for Underserved Communities: A Bayesian Approach to Online Restless Bandits AAAI 2025
Reinforcement Learning with Lookahead Information NIPS 2024
Finite-Time Frequentist Regret Bounds of Multi-Agent Thompson Sampling on Sparse Hypergraphs AAAI 2024
Towards Efficient and Optimal Covariance-Adaptive Algorithms for Combinatorial Semi-Bandits NIPS 2024
Improved Bayes Regret Bounds for Multi-Task Hierarchical Bayesian Bandit Algorithms NIPS 2024
Thompson Sampling for Real-Valued Combinatorial Pure Exploration of Multi-Armed Bandit AAAI 2024
The Choice of Noninformative Priors for Thompson Sampling in Multiparameter Bandit Models AAAI 2024
Improving sample efficiency of high dimensional Bayesian optimization with MCMC L4DC 2024
Sample Efficient Learning of Factored Embeddings of Tensor Fields AISTATS 2024
Thompson Sampling Itself is Differentially Private AISTATS 2024
Meta Learning in Bandits within shared affine Subspaces AISTATS 2024
Queueing Matching Bandits with Preference Feedback NIPS 2024
Optimal Exploration is no harder than Thompson Sampling AISTATS 2024
Near Optimal Adversarial Attacks on Stochastic Bandits and Defenses with Smoothed Responses AISTATS 2024
Accelerating Approximate Thompson Sampling with Underdamped Langevin Monte Carlo AISTATS 2024
Online Learning of Decision Trees with Thompson Sampling AISTATS 2024
Exploration via linearly perturbed loss minimisation AISTATS 2024