Iterative Sampling Methods for Sinkhorn Distributionally Robust Optimization

This article likely presents a novel approach to optimization, focusing on robustness against distributional shifts using Sinkhorn divergence and iterative sampling techniques. The core contribution would be the development and evaluation of these methods within the context of distributionally robust optimization. The use of 'ArXiv' as the source suggests this is a pre-print, indicating ongoing research and potential for future peer review and refinement.