1 citations · 1 across the 3 of their papers we have counts for
4 papers
Contextual Distributionally Robust Optimization with Causal and Continuous Structure: An Interpretable and Tractable Approach
Fenglin Zhang, Jie Wang
In this paper, we introduce a framework for contextual distributionally robust optimization (DRO) that considers the causal and continuous structure of the underlying distribution…
Iterative Sampling Methods for Sinkhorn Distributionally Robust Optimization
Jie Wang
Distributionally robust optimization (DRO) has emerged as a powerful paradigm for reliable decision-making under uncertainty. This paper focuses on DRO with ambiguity sets defined…
Regularization for Adversarial Robust Learning
Jie Wang, Rui Gao, Yao Xie
Despite the growing prevalence of artificial neural networks in real-world applications, their vulnerability to adversarial attacks remains a significant concern, which motivates u…
A Data-Driven Approach to Robust Hypothesis Testing Using Sinkhorn Uncertainty Sets
Jie Wang, Yao Xie
Hypothesis testing for small-sample scenarios is a practically important problem. In this paper, we investigate the robust hypothesis testing problem in a data-driven manner, where…