3 papers
stat.ME2025
Representation-Aware Distributionally Robust Optimization: A Knowledge Transfer Framework
Zitao Wang, Nian Si, Molei Liu
Distributionally robust optimization (DRO) protects statistical learning against distributional shifts by optimizing the worst-case performance over a set of perturbed distribution…
cs.LG2025
Knowledge-Guided Wasserstein Distributionally Robust Optimization
Zitao Wang, Ziyuan Wang, Molei Liu +1
Transfer learning is a popular strategy to leverage external knowledge and improve statistical efficiency, particularly with a limited target sample. We propose a novel knowledge-g…
stat.ME2024
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…