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Associative Reinforcement Learning using Linear Probabilistic Concepts
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Associative Reinforcement Learning using Linear Probabilistic Concepts (1999)Associative Reinforcement Learning using …Bypassing the Monster: A Faster and Simpler Optimal Algorithm for Contextual Bandits Under Realizability (2021)Bypassing the Monster: A Fast…Improved Algorithm on Online Clustering of Bandits (2019)Improved Algorithm on Online …A fully adaptive algorithm for pure exploration in linear bandits. (2018)A fully adaptive algorithm fo…Using upper confidence bounds for online learning (2002)Using upper confidence bounds…A Web marketing system with automatic pricing (2000)A Web marketing system with a…STOCHASTIC APPROXIMATION (2005)Some aspects of the sequential design of experiments (1952)Tracking the Best Expert (1998)Gambling in a rigged casino: The adversarial multi-armed bandit problem (2002)Sequential learning for optimal monitoring of multi-channel wireless networks (2011)Pure Exploration in Multi-armed Bandits Problems (2009)Improved Algorithms for Linear Stochastic Bandits (2011)Contextual Bandits with Linear Payoff Functions (2011)Regret Analysis of Stochastic and Nonstochastic Multi-armed Bandit Problems (2012)The Nonstochastic Multiarmed Bandit Problem (2002)An Empirical Evaluation of Thompson Sampling (2011)Bandit Algorithms (2020)Non-stationary Reinforcement Learning without Prior Knowledge: An Optimal Black-box Approach (2021)Offline Feature-Based Pricing Under Censored Demand: A Causal Inference Approach (2025)
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  • 2002Using upper confidence bounds for online learning53 cited
  • 2021Bypassing the Monster: A Faster and Simpler Optimal Algorithm for Contextual Bandits Under Realizability46 cited
  • 2019Improved Algorithm on Online Clustering of Bandits44 cited
  • 2018A fully adaptive algorithm for pure exploration in linear bandits.33 cited
  • 2000A Web marketing system with automatic pricing13 cited

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