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thompson sampling

237 papers

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Also known as

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

Sample Efficient Learning of Factored Embeddings of Tensor Fields AISTATS 2024
Randomized Exploration in Cooperative Multi-Agent Reinforcement Learning NIPS 2024
Code Repair with LLMs gives an Exploration-Exploitation Tradeoff NIPS 2024
Reinforcement Learning with Lookahead Information NIPS 2024
Thompson Sampling For Combinatorial Bandits: Polynomial Regret and Mismatched Sampling Paradox NIPS 2024
Exploration via linearly perturbed loss minimisation AISTATS 2024
The Choice of Noninformative Priors for Thompson Sampling in Multiparameter Bandit Models AAAI 2024
Cost-efficient Knowledge-based Question Answering with Large Language Models NIPS 2024
Optimizing Pessimism in Dynamic Treatment Regimes: A Bayesian Learning Approach AISTATS 2023
Towards Scalable and Robust Structured Bandits: A Meta-Learning Framework AISTATS 2023
Thompson Sampling with Diffusion Generative Prior ICML 2023
Optimality of Thompson Sampling with Noninformative Priors for Pareto Bandits ICML 2023
Multi-armed bandits for resource efficient, online optimization of language model pre-training: the use case of dynamic masking ACL 2023
Langevin Thompson Sampling with Logarithmic Communication: Bandits and Reinforcement Learning ICML 2023
Thompson Sampling with Less Exploration is Fast and Optimal ICML 2023
Double Doubly Robust Thompson Sampling for Generalized Linear Contextual Bandits AAAI 2023
Noise-Adaptive Thompson Sampling for Linear Contextual Bandits NIPS 2023
Incentivizing Exploration with Linear Contexts and Combinatorial Actions ICML 2023
Optimistic Thompson Sampling-based algorithms for episodic reinforcement learning UAI 2023
Causal Bandits for Linear Structural Equation Models JMLR 2023
Leveraging Demonstrations to Improve Online Learning: Quality Matters ICML 2023
Thompson Exploration with Best Challenger Rule in Best Arm Identification ACML 2023
Scalable Bayesian Optimization Using Vecchia Approximations of Gaussian Processes AISTATS 2023
TS-UCB: Improving on Thompson Sampling With Little to No Additional Computation AISTATS 2023
Tight Regret and Complexity Bounds for Thompson Sampling via Langevin Monte Carlo AISTATS 2023