1 citations · 1 across the 3 of their papers we have counts for
3 papers
stat.ME2024
Doubly robust causal inference through penalized bias-reduced estimation: combining non-probability samples with designed surveys
Jiacong Du, Xu Shi, Donglin Zeng +1
Causal inference on the average treatment effect (ATE) using non-probability samples, such as electronic health records (EHR), faces challenges from sample selection bias and high-…
cs.SE2024★ 1 cited
MLAD: A Unified Model for Multi-system Log Anomaly Detection
Runqiang Zang, Hongcheng Guo, Jian Yang +6
In spite of the rapid advancements in unsupervised log anomaly detection techniques, the current mainstream models still necessitate specific training for individual system dataset…
stat.ME2022
Doubly Robust Proximal Causal Inference under Confounded Outcome-Dependent Sampling
Kendrick Qijun Li, Xu Shi, Wang Miao +1
Unmeasured confounding and selection bias are often of concern in observational studies and may invalidate a causal analysis if not appropriately accounted for. Under outcome-depen…