4 citations · 8 across the 7 of their papers we have counts for
8 papers
Transformation-Invariant Learning of Optimal Individualized Decision Rules with Time-to-Event Outcomes
Yu Zhou, Lan Wang, Rui Song +1
In many important applications of precision medicine, the outcome of interest is time to an event (e.g., death, relapse of disease) and the primary goal is to identify the optimal…
Adaptive Semi-Supervised Inference for Optimal Treatment Decisions with Electronic Medical Record Data
Kevin Gunn, Wenbin Lu, Rui Song
A treatment regime is a rule that assigns a treatment to patients based on their covariate information. Recently, estimation of the optimal treatment regime that yields the greates…
Towards Scalable and Robust Structured Bandits: A Meta-Learning Framework
Runzhe Wan, Lin Ge, Rui Song
Online learning in large-scale structured bandits is known to be challenging due to the curse of dimensionality. In this paper, we propose a unified meta-learning framework for a g…
Reinforcement Learning with Heterogeneous Data: Estimation and Inference
Elynn Y. Chen, Rui Song, Michael I. Jordan
Reinforcement Learning (RL) has the promise of providing data-driven support for decision-making in a wide range of problems in healthcare, education, business, and other domains.…
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…
Online Testing of Subgroup Treatment Effects Based on Value Difference
Miao Yu, Wenbin Lu, Rui Song
Online A/B testing plays a critical role in the high-tech industry to guide product development and accelerate innovation. It performs a null hypothesis statistical test to determi…