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06/13/2023
Kernelized Reinforcement Learning with Order Optimal Regret Bounds
Reinforcement learning (RL) has shown empirical success in various real ...
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05/01/2023
First- and Second-Order Bounds for Adversarial Linear Contextual Bandits
We consider the adversarial linear contextual bandit setting, which allo...
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05/27/2022
Lifting the Information Ratio: An Information-Theoretic Analysis of Thompson Sampling for Contextual Bandits
We study the Bayesian regret of the renowned Thompson Sampling algorithm...
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09/24/2021
Learning to maximize global influence from local observations
We study a family online influence maximization problems where in a sequ...
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07/03/2020
Online learning in MDPs with linear function approximation and bandit feedback
We consider an online learning problem where the learner interacts with ...
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02/01/2020
Efficient and Robust Algorithms for Adversarial Linear Contextual Bandits
We consider an adversarial variant of the classic K-armed linear context...
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05/28/2018