5 papers
Robust Learning of Heterogeneous Dynamic Systems
Shuoxun Xu, Zijian Guo, Brooke R. Staveland +2
Ordinary differential equations (ODEs) provide a powerful framework for modeling dynamic systems arising in a wide range of scientific domains. However, most existing ODE methods f…
StablePCA: Distributionally Robust Learning of Shared Representations from Multi-Source Data
Zhenyu Wang, Molei Liu, Jing Lei +2
When synthesizing multi-source high-dimensional data, a key objective is to extract low-dimensional representations that effectively approximate the original features across differ…
Adversarial Drift-Aware Predictive Transfer: Toward Durable Clinical AI
Xin Xiong, Zijian Guo, Haobo Zhu +4
Clinical AI systems frequently suffer performance decay post-deployment due to temporal data shifts, such as evolving populations, diagnostic coding updates (e.g., ICD-9 to ICD-10)…
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…
Multi-source Stable Variable Importance Measure via Adversarial Machine Learning
Zitao Wang, Nian Si, Zijian Guo +1
The quantification and inference of predictive importance for exposure covariates have recently gained significant attention in the context of interpretable machine learning. Conte…