1 citations · 1 across the 7 of their papers we have counts for
7 papers
An optimal two-step estimation approach for two-phase studies
Qingning Zhou, Kin Yau Wong
Two-phase sampling is commonly adopted for reducing cost and improving estimation efficiency. In many two-phase studies, the outcome and some cheap covariates are observed for a la…
Nonlinear Causal Discovery through a Sequential Edge Orientation Approach
Stella Huang, Qing Zhou
Recent advances have established the identifiability of a directed acyclic graph (DAG) under additive noise models (ANMs), spurring the development of various causal discovery meth…
The Correlation Thresholding Algorithm for Exploratory Factor Analysis
Dale S. Kim, Audrey Lu, Qing Zhou
Exploratory factor analysis is often used in the social sciences to estimate potential measurement models. To do this, several important issues need to be addressed: (1) determinin…
Causal Bandit Over Unknown Graphs: Upper Confidence Bounds With Backdoor Adjustment
Yijia Zhao, Qing Zhou
The causal bandit problem seeks to identify, through sequential experimentation, an intervention that maximizes the expected reward in a causal system modeled by a directed acyclic…
Causal Discovery on Dependent Binary Data
Alex Chen, Qing Zhou
The assumption of independence between observations (units) in a dataset is prevalent across various methodologies for learning causal graphical models. However, this assumption of…
Coordinated Multi-Neighborhood Learning on a Directed Acyclic Graph
Stephen Smith, Qing Zhou
Learning the structure of causal directed acyclic graphs (DAGs) is useful in many areas of machine learning and artificial intelligence, with wide applications. However, in the hig…
Structure Learning of Latent Factors via Clique Search on Correlation Thresholded Graphs
Dale S. Kim, Qing Zhou
Despite the widespread application of latent factor analysis, existing methods suffer from the following weaknesses: requiring the number of factors to be known, lack of theoretica…