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https://openreview.net/forum?id=BnV2M2WFaY&referrer=%5Bthe%20profile%20of%20Tianhao%20Wang%5D(%2Fprofile%3Fid%3D~Tianhao_Wang1) Noise-Adaptive Thompson Sampling for Linear Contextual Bandits | OpenReview Linear contextual bandits represent a fundamental class of models with numerous real-world applications, and it is critical to develop algorithms that can... thompson sampling contextual bandits noise adaptive linear https://www.tensorflow.org/agents/api_docs/python/tf_agents/bandits/policies/linear_thompson_sampling_policy/LinearThompsonSamplingPolicy tf_agents.bandits.policies.linear_thompson_sampling_policy.LinearThompsonSamplingPolicy |... Linear Thompson Sampling Policy. thompson sampling tf agents bandits policies https://arxiv.org/abs/2307.10167 [2307.10167] VITS : Variational Inference Thompson Sampling for contextual bandits Abstract page for arXiv paper 2307.10167: VITS : Variational Inference Thompson Sampling for contextual bandits variational inference thompson sampling vits contextual bandits https://openreview.net/forum?id=LxX6l3I6iN Thompson Sampling with Less Exploration is Fast and Optimal | OpenReview We propose $\epsilon$-Exploring Thompson Sampling ($\epsilon$-TS), a modified version of the Thompson Sampling (TS) algorithm for multi-armed bandits. In... thompson sampling less exploration fast optimal https://openreview.net/forum?id=lXD6Ju3rx2G&referrer=%5Bthe%20profile%20of%20Ciamac%20C.%20Moallemi%5D(%2Fprofile%3Fid%3D~Ciamac_C._Moallemi1) Policy Gradient Optimization of Thompson Sampling Policies | OpenReview We study the use of policy gradient algorithms to optimize over a class of generalized Thompson sampling policies. Our central insight is to view the posterior... thompson sampling policy gradient optimization policies https://deepai.org/publication/adaptive-thompson-sampling-stacks-for-memory-bounded-open-loop-planning Adaptive Thompson Sampling Stacks for Memory Bounded Open-Loop Planning | DeepAI Jul 11, 2019 - 07/11/19 - We propose Stable Yet Memory Bounded Open-Loop (SYMBOL) planning, a general memory bounded approach to partially observable open-l... thompson sampling open loop adaptive stacks https://www.merlot.org/merlot/viewMaterial.htm?id=969458 Thompson Sampling: a provably good Bayesian heuristic for bandit problems thompson sampling provably good bayesian heuristic https://deepai.org/publication/thompson-sampling-for-a-fatigue-aware-online-recommendation-system Thompson Sampling for a Fatigue-aware Online Recommendation System | DeepAI Jan 23, 2019 - 01/23/19 - In this paper we consider an online recommendation setting, where a platform recommends a sequence of items to its users at every ... thompson sampling recommendation system fatigue aware online https://deepai.org/publication/a-unifying-theory-of-thompson-sampling-for-continuous-risk-averse-bandits A Unifying Theory of Thompson Sampling for Continuous Risk-Averse Bandits | DeepAI Aug 25, 2021 - 08/25/21 - This paper unifies the design and simplifies the analysis of risk-averse Thompson sampling algorithms for the multi-armed bandit p... unifying theory thompson sampling https://openreview.net/forum?id=Z_FEDOjQ1T&referrer=%5Bthe%20profile%20of%20Ciamac%20C.%20Moallemi%5D(%2Fprofile%3Fid%3D~Ciamac_C._Moallemi1) Thompson Sampling with Information Relaxation Penalties | OpenReview We consider a finite-horizon multi-armed bandit (MAB) problem in a Bayesian setting, for which we propose an information relaxation sampling framework. With... thompson sampling information relaxation penalties openreview https://deepai.org/publication/a-change-detection-based-thompson-sampling-framework-for-non-stationary-bandits A Change-Detection Based Thompson Sampling Framework for Non-Stationary Bandits | DeepAI Sep 6, 2020 - 09/06/20 - We consider a non-stationary two-armed bandit framework and propose a change-detection based Thompson sampling (TS) algorithm, nam... a change thompson sampling https://openreview.net/forum?id=rdMQrE-loT5 Parallelizing Thompson Sampling | OpenReview Batch Thompson Sampling thompson sampling openreview https://deepai.org/publication/thompson-sampling-for-bandit-learning-in-matching-markets Thompson Sampling for Bandit Learning in Matching Markets | DeepAI Apr 26, 2022 - 04/26/22 - The problem of two-sided matching markets has a wide range of real-world applications and has been extensively studied in the lite... thompson sampling bandit learning matching markets https://arxiv.org/abs/1611.05724 [1611.05724] Unimodal Thompson Sampling for Graph-Structured Arms Abstract page for arXiv paper 1611.05724: Unimodal Thompson Sampling for Graph-Structured Arms thompson sampling graph structured arms https://deepai.org/machine-learning-glossary-and-terms/thompson-sampling Thompson Sampling Definition | DeepAI May 17, 2019 - Thompson sampling is a heuristic learning algorithm that chooses an action which maximizes the expected reward for a randomly assigned belief. thompson sampling definition deepai https://arxiv.org/abs/1908.04970 [1908.04970] Thompson Sampling with Approximate Inference Abstract page for arXiv paper 1908.04970: Thompson Sampling with Approximate Inference thompson sampling approximate inference https://openreview.net/forum?id=BhFp6cFwDq Bootstrap Your Conversions: Thompson Sampling for Partially Observable Delayed Rewards | OpenReview This paper presents a novel approach to address contextual bandit problems with partially observable, delayed feedback by introducing an approximate Thompson... thompson sampling bootstrap conversions https://arxiv.org/abs/2410.04988 [2410.04988] Efficient Model-Based Reinforcement Learning Through Optimistic Thompson Sampling Abstract page for arXiv paper 2410.04988: Efficient Model-Based Reinforcement Learning Through Optimistic Thompson Sampling reinforcement learning efficient model based https://arxiv.org/abs/2510.20725 [2510.20725] No-Regret Thompson Sampling for Finite-Horizon Markov Decision Processes with Gaussian... Abstract page for arXiv paper 2510.20725: No-Regret Thompson Sampling for Finite-Horizon Markov Decision Processes with Gaussian Processes https://openreview.net/forum?id=ulqMdBThHsC The Hardness Analysis of Thompson Sampling for Combinatorial Semi-bandits with Greedy Oracle |... Thompson sampling (TS) has attracted a lot of interest in the bandit area. It was introduced in the 1930s but has not been theoretically proven until recent... https://arxiv.org/abs/2303.09033 [2303.09033] Only Pay for What Is Uncertain: Variance-Adaptive Thompson Sampling Abstract page for arXiv paper 2303.09033: Only Pay for What Is Uncertain: Variance-Adaptive Thompson Sampling pay for what is