17 citations · 71 across the 33 of their papers we have counts for
6 papers · 1 filter
An Online Sequential Test for Qualitative Treatment Effects
Chengchun Shi, Shikai Luo, Hongtu Zhu +1
Tech companies (e.g., Google or Facebook) often use randomized online experiments and/or A/B testing primarily based on the average treatment effects to compare their new product w…
Jump Interval-Learning for Individualized Decision Making
Hengrui Cai, Chengchun Shi, Rui Song +1
An individualized decision rule (IDR) is a decision function that assigns each individual a given treatment based on his/her observed characteristics. Most of the existing works in…
A Minimax Learning Approach to Off-Policy Evaluation in Confounded Partially Observable Markov Decision Processes
Chengchun Shi, Masatoshi Uehara, Jiawei Huang +1
We consider off-policy evaluation (OPE) in Partially Observable Markov Decision Processes (POMDPs), where the evaluation policy depends only on observable variables and the behavio…
Pattern Transfer Learning for Reinforcement Learning in Order Dispatching
Runzhe Wan, Sheng Zhang, Chengchun Shi +2
Order dispatch is one of the central problems to ride-sharing platforms. Recently, value-based reinforcement learning algorithms have shown promising performance on this problem. H…
Deeply-Debiased Off-Policy Interval Estimation
Chengchun Shi, Runzhe Wan, Victor Chernozhukov +1
Off-policy evaluation learns a target policy's value with a historical dataset generated by a different behavior policy. In addition to a point estimate, many applications would be…
Testing Directed Acyclic Graph via Structural, Supervised and Generative Adversarial Learning
Chengchun Shi, Yunzhe Zhou, Lexin Li
In this article, we propose a new hypothesis testing method for directed acyclic graph (DAG). While there is a rich class of DAG estimation methods, there is a relative paucity of…