Finite-Sample Guarantees for Wasserstein Distributionally Robust Optimization: Breaking the Curse of Dimensionality

9 September 2020

Papers citing "Finite-Sample Guarantees for Wasserstein Distributionally Robust Optimization: Breaking the Curse of Dimensionality"

12 / 12 papers shown

Title
Wasserstein Distributionally Robust Nonparametric Regression Changyu Liu Yuling Jiao Junhui Wang Jian Huang OOD 31 0 0 12 May 2025
Universal generalization guarantees for Wasserstein distributionally robust models Tam Le Jérome Malick OOD 45 2 0 28 Jan 2025
New Perspectives on Regularization and Computation in Optimal Transport-Based Distributionally Robust Optimization Soroosh Shafieezadeh-Abadeh Liviu Aolaritei Florian Dorfler Daniel Kuhn 54 20 0 31 Dec 2024
Evaluating Model Performance Under Worst-case Subpopulations Mike Li Hongseok Namkoong Shangzhou Xia 37 17 0 01 Jul 2024
Nonlinear Distributionally Robust Optimization Mohammed Rayyan Sheriff Peyman Mohajerin Esfahani 32 2 0 05 Jun 2023
Learning Against Distributional Uncertainty: On the Trade-off Between Robustness and Specificity Shixiong Wang Haowei Wang Xinke Li Jean Honorio OOD 65 1 0 31 Jan 2023
Instance-Dependent Generalization Bounds via Optimal Transport Songyan Hou Parnian Kassraie Anastasis Kratsios Andreas Krause Jonas Rothfuss 22 6 0 02 Nov 2022
Sinkhorn Distributionally Robust Optimization Jie Wang Rui Gao Yao Xie 40 35 0 24 Sep 2021
Robust Hypothesis Testing with Wasserstein Uncertainty Sets Liyan Xie Rui Gao Yao Xie OOD 33 9 0 29 May 2021
Reliable Off-policy Evaluation for Reinforcement Learning Jie Wang Rui Gao H. Zha OffRL 17 11 0 08 Nov 2020
Linear Convergence of Gradient and Proximal-Gradient Methods Under the Polyak-Łojasiewicz Condition Hamed Karimi J. Nutini Mark W. Schmidt 136 1,198 0 16 Aug 2016
Sample Out-Of-Sample Inference Based on Wasserstein Distance Jose H. Blanchet Yang Kang 25 35 0 04 May 2016