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Improved Corruption Robust Algorithms for Episodic Reinforcement Learning
We study episodic reinforcement learning under unknown adversarial corru...
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More Practical and Adaptive Algorithms for Online Quantum State Learning
Online quantum state learning is a recently proposed problem by Aaronson...
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Fair Contextual Multi-Armed Bandits: Theory and Experiments
When an AI system interacts with multiple users, it frequently needs to ...
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Online and Bandit Algorithms for Nonstationary Stochastic Saddle-Point Optimization
Saddle-point optimization problems are an important class of optimizatio...
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Reinforcement Learning with Fairness Constraints for Resource Distribution in Human-Robot Teams
Much work in robotics and operations research has focused on optimal res...
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A New Algorithm for Non-stationary Contextual Bandits: Efficient, Optimal, and Parameter-free
We propose the first contextual bandit algorithm that is parameter-free,...
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Yifang Chen
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