Representation-Aware Distributionally Robust Optimization: A Knowledge Transfer Framework
表示感知的分布鲁棒优化:一个知识迁移框架
Distributionally robust optimization (DRO) protects statistical learning against distributional shifts by optimizing the worst-case performance over a set of perturbed distributions. However, standard DRO formulations often treat all feature perturbations equally. This can be unnecessarily conservative when external knowledge suggests that the predictive signal is embedded in a low-dimensional representation of covariates. We propose REpresentation-Aware Distributionally…