67 citations · 111 across the 41 of their papers we have counts for
10 papers · 1 filter
Off-Policy Evaluation for Missingness-Aware Policies in MDPs with Rewards Missing Not at Random
Ziheng Wei, Annie Qu, Rui Miao
In offline Reinforcement Learning, immediate rewards in logged batch data are often unobserved due to sparse or irregular record-keeping, or censored beyond certain reward values.…
Multi-Task Learning with Covariate-Overlap Regularization
Yang Sui, Qi Xu, Yang Bai +1
Multi-task learning improves data efficiency by sharing information across related tasks, but indiscriminate sharing can be harmful when their covariate distributions and response…
Reinforcement Learning for Individual Optimal Policy from Heterogeneous Data
Rui Miao, Babak Shahbaba, Annie Qu
Offline reinforcement learning (RL) aims to find optimal policies in dynamic environments in order to maximize the expected total rewards by leveraging pre-collected data. Learning…
Stackelberg Batch Policy Learning
Wenzhuo Zhou, Annie Qu
Batch reinforcement learning (RL) defines the task of learning from a fixed batch of data lacking exhaustive exploration. Worst-case optimality algorithms, which calibrate a value-…
Distributional Shift-Aware Off-Policy Interval Estimation: A Unified Error Quantification Framework
Wenzhuo Zhou, Yuhan Li, Ruoqing Zhu +1
We study high-confidence off-policy evaluation in the context of infinite-horizon Markov decision processes, where the objective is to establish a confidence interval (CI) for the…
Stage-Aware Learning for Dynamic Treatments
Hanwen Ye, Wenzhuo Zhou, Ruoqing Zhu +1
Recent advances in dynamic treatment regimes (DTRs) facilitate the search for optimal treatments, which are tailored to individuals' specific needs and able to maximize their expec…
A Model-Agnostic Graph Neural Network for Integrating Local and Global Information
Wenzhuo Zhou, Annie Qu, Keiland W. Cooper +2
Graph Neural Networks (GNNs) have achieved promising performance in a variety of graph-focused tasks. Despite their success, however, existing GNNs suffer from two significant limi…
Query-augmented Active Metric Learning
Yujia Deng, Yubai Yuan, Haoda Fu +1
In this paper we propose an active metric learning method for clustering with pairwise constraints. The proposed method actively queries the label of informative instance pairs, wh…
Individualized Multilayer Tensor Learning with An Application in Imaging Analysis
Xiwei Tang, Xuan Bi, Annie Qu
This work is motivated by multimodality breast cancer imaging data, which is quite challenging in that the signals of discrete tumor-associated microvesicles (TMVs) are randomly di…
Multilayer tensor factorization with applications to recommender systems
Xuan Bi, Annie Qu, Xiaotong Shen
Recommender systems have been widely adopted by electronic commerce and entertainment industries for individualized prediction and recommendation, which benefit consumers and impro…