6 papers
Guided Uncertainty-Aware Robust Domain Transfer
Xin Xiong, Zijian Guo, Tianxi Cai
Artificial intelligence models deployed as clinical decision support tools often suffer substantial performance degradation over time and across institutions due to covariate shift…
Unveiling Invariant and Transferable Latent Factors Across Heterogeneous Environments via ATLAS
Yihong Gu, Katherine Liao, Tianxi Cai
This paper considers a multi-environment factor model in which high-dimensional covariates are collected from heterogeneous environments, with auxiliary labels available in a subse…
Federated One-Shot Ensemble Clustering
Rui Duan, Xin Xiong, Jueyi Liu +2
Cluster analysis across multiple institutions poses significant challenges due to data-sharing restrictions. To overcome these limitations, we introduce the Federated One-shot Ense…
Domain Adaptation Optimized for Robustness in Mixture Populations
Keyao Zhan, Xin Xiong, Zijian Guo +2
While domain adaptation methods address data shifts, most assume target populations align with at least one source population, neglecting mixtures that combine sources influenced b…
Semi-supervised Estimation of Event Rate with Doubly-censored Survival Data
Yang Wang, Qingning Zhou, Tianxi Cai +1
Electronic Health Record (EHR) has emerged as a valuable source of data for translational research. To leverage EHR data for risk prediction and subsequently clinical decision supp…
Guided Adversarial Robust Transfer Learning with Source Mixing
Xin Xiong, Zijian Guo, Tianxi Cai
Transfer learning is a critical technique that enables the application of knowledge gained from existing tasks or domains to improve performance on a new one, reducing the need for…