9 citations · 14 across the 5 of their papers we have counts for
9 papers
Separable pathway effects of semi-competing risks using multi-state models
Yuhao Deng, Yi Wang, Xiang Zhan +1
Semi-competing risks refer to the phenomenon where a primary event (such as mortality) can ``censor'' an intermediate event (such as relapse of a disease), but not vice versa. Unde…
A Semi-Synthetic Dataset Generation Framework for Causal Inference in Recommender Systems
Yan Lyu, Sunhao Dai, Peng Wu +7
Accurate recommendation and reliable explanation are two key issues for modern recommender systems. However, most recommendation benchmarks only concern the prediction of user-item…
On the Opportunity of Causal Learning in Recommendation Systems: Foundation, Estimation, Prediction and Challenges
Peng Wu, Haoxuan Li, Yuhao Deng +6
Recently, recommender system (RS) based on causal inference has gained much attention in the industrial community, as well as the states of the art performance in many prediction a…
Causal Inference with Truncation-by-Death and Unmeasured Confounding
Yuhao Deng, Yingjun Chang, Xiao-Hua Zhou
Clinical studies sometimes encounter truncation by death, rendering outcomes undefined. Statistical analysis based solely on observed survivors may give biased results because the…
Model-Assisted Inference for Covariate-Specific Treatment Effects with High-dimensional Data
Peng Wu, Zhiqiang Tan, Wenjie Hu +1
Covariate-specific treatment effects (CSTEs) represent heterogeneous treatment effects across subpopulations defined by certain selected covariates. In this article, we consider ma…
On rank estimators in increasing dimensions
Yanqin Fan, Fang Han, Wei Li +1
The family of rank estimators, including Han's maximum rank correlation (Han, 1987) as a notable example, has been widely exploited in studying regression problems. For these estim…