A Data-Driven Approach to Robust Hypothesis Testing Using Sinkhorn
Uncertainty Sets

A Data-Driven Approach to Robust Hypothesis Testing Using Sinkhorn Uncertainty Sets

9 February 2022

Yao Xie

Papers citing "A Data-Driven Approach to Robust Hypothesis Testing Using Sinkhorn Uncertainty Sets"

9 / 9 papers shown

Title
Gaussian Derivative Change-point Detection for Early Warnings of Industrial System Failures Hao Zhao Rong Pan 53 0 0 29 Oct 2024
Robust Kernel Hypothesis Testing under Data Corruption Antonin Schrab Ilmun Kim 48 3 0 30 May 2024
Statistical and Computational Guarantees of Kernel Max-Sliced Wasserstein Distances Jie Wang M. Boedihardjo Yao Xie 54 1 0 24 May 2024
Non-Convex Robust Hypothesis Testing using Sinkhorn Uncertainty Sets Jie Wang Rui Gao Yao Xie 56 1 0 21 Mar 2024
Flow-based Distributionally Robust Optimization Chen Xu Jonghyeok Lee Xiuyuan Cheng Yao Xie OOD 36 4 0 30 Oct 2023
Distributionally Robust Quickest Change Detection using Wasserstein Uncertainty Sets Liyan Xie Yuchen Liang V. Veeravalli 25 1 0 28 Sep 2023
Exact Generalization Guarantees for (Regularized) Wasserstein Distributionally Robust Models Waïss Azizian F. Iutzeler J. Malick OOD 41 8 0 26 May 2023
Robust Multi-Hypothesis Testing with Moment Constrained Uncertainty Sets A. Magesh Zhongchang Sun V. Veeravalli Shaofeng Zou 21 1 0 23 Oct 2022
Kernel Robust Hypothesis Testing Zhongchang Sun Shaofeng Zou OOD 11 13 0 23 Mar 2022