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06/14/2023
Off-policy Evaluation in Doubly Inhomogeneous Environments
This work aims to study off-policy evaluation (OPE) under scenarios wher...
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05/26/2023
A Policy Gradient Method for Confounded POMDPs
In this paper, we propose a policy gradient method for confounded partia...
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03/24/2023
Sequential Knockoffs for Variable Selection in Reinforcement Learning
In real-world applications of reinforcement learning, it is often challe...
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02/24/2023
Personalized Pricing with Invalid Instrumental Variables: Identification, Estimation, and Policy Learning
Pricing based on individual customer characteristics is widely used to m...
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02/08/2023
PASTA: Pessimistic Assortment Optimization
We consider a class of assortment optimization problems in an offline da...
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01/30/2023
STEEL: Singularity-aware Reinforcement Learning
Batch reinforcement learning (RL) aims at finding an optimal policy in a...
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12/23/2022
Offline Reinforcement Learning for Human-Guided Human-Machine Interaction with Private Information
Motivated by the human-machine interaction such as training chatbots for...
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11/12/2022
RISE: Robust Individualized Decision Learning with Sensitive Variables
This paper introduces RISE, a robust individualized decision learning fr...
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10/26/2022
Optimizing Pessimism in Dynamic Treatment Regimes: A Bayesian Learning Approach
In this article, we propose a novel pessimism-based Bayesian learning me...
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09/29/2022
Blessing from Experts: Super Reinforcement Learning in Confounded Environments
We introduce super reinforcement learning in the batch setting, which ta...
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09/21/2022
Off-Policy Evaluation for Episodic Partially Observable Markov Decision Processes under Non-Parametric Models
We study the problem of off-policy evaluation (OPE) for episodic Partial...
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09/18/2022
Offline Reinforcement Learning with Instrumental Variables in Confounded Markov Decision Processes
We study the offline reinforcement learning (RL) in the face of unmeasur...
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07/23/2022
Change Point Detection for High-dimensional Linear Models: A General Tail-adaptive Approach
We study the change point detection problem for high-dimensional linear ...
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01/17/2022
On Well-posedness and Minimax Optimal Rates of Nonparametric Q-function Estimation in Off-policy Evaluation
We study the off-policy evaluation (OPE) problem in an infinite-horizon ...
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11/29/2021
Pessimistic Model Selection for Offline Deep Reinforcement Learning
Deep Reinforcement Learning (DRL) has demonstrated great potentials in s...
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10/17/2021
Rejoinder: Learning Optimal Distributionally Robust Individualized Treatment Rules
We thank the opportunity offered by editors for this discussion and the ...
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09/10/2021
Projected State-action Balancing Weights for Offline Reinforcement Learning
Offline policy evaluation (OPE) is considered a fundamental and challeng...
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05/03/2021
Proximal Learning for Individualized Treatment Regimes Under Unmeasured Confounding
Data-driven individualized decision making has recently received increas...
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11/09/2020
Robust Batch Policy Learning in Markov Decision Processes
We study the sequential decision making problem in Markov decision proce...
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07/23/2020
Batch Policy Learning in Average Reward Markov Decision Processes
We consider the batch (off-line) policy learning problem in the infinite...
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06/26/2020
Learning Optimal Distributionally Robust Individualized Treatment Rules
Recent development in the data-driven decision science has seen great ad...
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10/06/2019
Statistical Analysis of Stationary Solutions of Coupled Nonconvex Nonsmooth Empirical Risk Minimization
This paper has two main goals: (a) establish several statistical propert...
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08/27/2019
Estimation of Individualized Decision Rules Based on an Optimized Covariate-Dependent Equivalent of Random Outcomes
Recent exploration of optimal individualized decision rules (IDRs) for p...
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03/11/2019