310 citations · 2k across the 67 of their papers we have counts for
5 papers · 2 filters
Statistical Inference for Online Decision Making via Stochastic Gradient Descent
Haoyu Chen, Wenbin Lu, Rui Song
Online decision making aims to learn the optimal decision rule by making personalized decisions and updating the decision rule recursively. It has become easier than before with th…
Statistical Inference for Online Decision-Making: In a Contextual Bandit Setting
Haoyu Chen, Wenbin Lu, Rui Song
Online decision-making problem requires us to make a sequence of decisions based on incremental information. Common solutions often need to learn a reward model of different action…
Deep Jump Learning for Off-Policy Evaluation in Continuous Treatment Settings
Hengrui Cai, Chengchun Shi, Rui Song +1
We consider off-policy evaluation (OPE) in continuous treatment settings, such as personalized dose-finding. In OPE, one aims to estimate the mean outcome under a new treatment dec…
Does the Markov Decision Process Fit the Data: Testing for the Markov Property in Sequential Decision Making
Chengchun Shi, Runzhe Wan, Rui Song +2
The Markov assumption (MA) is fundamental to the empirical validity of reinforcement learning. In this paper, we propose a novel Forward-Backward Learning procedure to test MA in s…
Statistical Inference of the Value Function for Reinforcement Learning in Infinite Horizon Settings
C. Shi, S. Zhang, W. Lu +1
Reinforcement learning is a general technique that allows an agent to learn an optimal policy and interact with an environment in sequential decision making problems. The goodness…