4 papers · 1 filter
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…
Statistical and Computational Guarantees of Kernel Max-Sliced Wasserstein Distances
Jie Wang, March Boedihardjo, Yao Xie
Optimal transport has been very successful for various machine learning tasks; however, it is known to suffer from the curse of dimensionality. Hence, dimensionality reduction is d…
Variable Selection for Kernel Two-Sample Tests
Jie Wang, Santanu S. Dey, Yao Xie
We consider the variable selection problem for two-sample tests, aiming to select the most informative variables to determine whether two collections of samples follow the same dis…