25 citations · 33 across the 8 of their papers we have counts for
4 papers · 1 filter
Instance-Dependent Complexity of Contextual Bandits and Reinforcement Learning: A Disagreement-Based Perspective
Dylan J. Foster, Alexander Rakhlin, David Simchi-Levi +1
In the classical multi-armed bandit problem, instance-dependent algorithms attain improved performance on "easy" problems with a gap between the best and second-best arm. Are simil…
Provably More Efficient Q-Learning in the One-Sided-Feedback/Full-Feedback Settings
Xiao-Yue Gong, David Simchi-Levi
Motivated by the episodic version of the classical inventory control problem, we propose a new Q-learning-based algorithm, Elimination-Based Half-Q-Learning (HQL), that enjoys impr…
Reinforcement Learning for Non-Stationary Markov Decision Processes: The Blessing of (More) Optimism
Wang Chi Cheung, David Simchi-Levi, Ruihao Zhu
We consider un-discounted reinforcement learning (RL) in Markov decision processes (MDPs) under drifting non-stationarity, i.e., both the reward and state transition distributions…
Online Learning and Optimization for Revenue Management Problems with Add-on Discounts
David Simchi-Levi, Rui Sun, Huanan Zhang
We study in this paper a revenue management problem with add-on discounts. The problem is motivated by the practice in the video game industry, where a retailer offers discounts on…