Wasserstein Distributionally Robust Optimization: Theory and Applications in Machine Learning

23 August 2019

Daniel Kuhn

Peyman Mohajerin Esfahani

Viet Anh Nguyen

Soroosh Shafieezadeh-Abadeh

OOD

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Papers citing "Wasserstein Distributionally Robust Optimization: Theory and Applications in Machine Learning"

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Title
Wasserstein Distributionally Robust Regret Optimization Lukas-Benedikt Fiechtner Jose Blanchet 27 0 0 15 Apr 2025
Achievable distributional robustness when the robust risk is only partially identified Julia Kostin Nicola Gnecco Fanny Yang 73 3 0 04 Feb 2025
Universal generalization guarantees for Wasserstein distributionally robust models Tam Le Jérome Malick OOD 53 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 58 20 0 31 Dec 2024
Unsupervised Training of Convex Regularizers using Maximum Likelihood Estimation Hongwei Tan Ziruo Cai Marcelo Pereyra Subhadip Mukherjee Junqi Tang Carola-Bibiane Schönlieb SSL 70 1 0 08 Apr 2024
Conformal Predictive Programming for Chance Constrained Optimization Yiqi Zhao Xinyi Yu Matteo Sesia Lars Lindemann Lars Lindemann 42 3 0 12 Feb 2024
Algorithms for mean-field variational inference via polyhedral optimization in the Wasserstein space Yiheng Jiang Sinho Chewi Aram-Alexandre Pooladian 29 7 0 05 Dec 2023
Learning Optimal Classification Trees Robust to Distribution Shifts Nathan Justin S. Aghaei Andrés Gómez P. Vayanos OOD 35 0 0 26 Oct 2023
Nonlinear Distributionally Robust Optimization Mohammed Rayyan Sheriff Peyman Mohajerin Esfahani 32 2 0 05 Jun 2023
Twice Regularized Markov Decision Processes: The Equivalence between Robustness and Regularization E. Derman Yevgeniy Men M. Geist Shie Mannor 39 1 0 12 Mar 2023
Diagnosing Model Performance Under Distribution Shift Tiffany Cai Hongseok Namkoong Steve Yadlowsky 37 27 0 03 Mar 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
On adversarial robustness and the use of Wasserstein ascent-descent dynamics to enforce it Camilo A. Garcia Trillos Nicolas García Trillos 16 5 0 09 Jan 2023
A Distributionally Robust Optimization Framework for Extreme Event Estimation Yuanlu Bai H. Lam Xinyu Zhang 28 4 0 03 Jan 2023
Distributional Robustness Bounds Generalization Errors Shixiong Wang Haowei Wang OOD 32 4 0 20 Dec 2022
Stochastic Optimization for Spectral Risk Measures Ronak R. Mehta Vincent Roulet Krishna Pillutla Lang Liu Zaïd Harchaoui 32 6 0 10 Dec 2022
Path Planning Using Wassertein Distributionally Robust Deep Q-learning Cem Alptürk Venkatraman Renganathan OOD 16 0 0 04 Nov 2022
Instance-Dependent Generalization Bounds via Optimal Transport Songyan Hou Parnian Kassraie Anastasis Kratsios Andreas Krause Jonas Rothfuss 22 6 0 02 Nov 2022
Distributed Distributionally Robust Optimization with Non-Convex Objectives Yang Jiao Kai Yang Dongjin Song 27 11 0 14 Oct 2022
An Optimal Transport Approach to Personalized Federated Learning Farzan Farnia Amirhossein Reisizadeh Ramtin Pedarsani Ali Jadbabaie OT OOD FedML 31 12 0 06 Jun 2022
On the Generalization of Wasserstein Robust Federated Learning Tung Nguyen Tuan Dung Nguyen Long Tan Le Canh T. Dinh N. H. Tran OOD FedML 21 6 0 03 Jun 2022
An improved central limit theorem and fast convergence rates for entropic transportation costs E. del Barrio Alberto González Sanz Jean-Michel Loubes Jonathan Niles-Weed OT 34 32 0 19 Apr 2022
Expert-Calibrated Learning for Online Optimization with Switching Costs Pengfei Li Jianyi Yang Shaolei Ren 24 11 0 18 Apr 2022
Global-Local Regularization Via Distributional Robustness Hoang Phan Trung Le Trung-Nghia Phung Tu Bui Nhat Ho Dinh Q. Phung OOD 16 12 0 01 Mar 2022
A Unified Wasserstein Distributional Robustness Framework for Adversarial Training Tu Bui Trung Le Quan Hung Tran He Zhao Dinh Q. Phung AAML OOD 31 42 0 27 Feb 2022
Distributionally Robust Fair Principal Components via Geodesic Descents Hieu Vu Toan M. Tran Man-Chung Yue Viet Anh Nguyen 11 14 0 07 Feb 2022
Rates of convergence for nonparametric estimation of singular distributions using generative adversarial networks Minwoo Chae GAN 32 4 0 07 Feb 2022
Counterfactual Plans under Distributional Ambiguity N. Bui D. Nguyen Viet Anh Nguyen 62 24 0 29 Jan 2022
Human Imperceptible Attacks and Applications to Improve Fairness Xinru Hua Huanzhong Xu Jose H. Blanchet V. Nguyen AAML 19 3 0 30 Nov 2021
Sinkhorn Distributionally Robust Optimization Jie Wang Rui Gao Yao Xie 46 35 0 24 Sep 2021
On the regularized risk of distributionally robust learning over deep neural networks Camilo A. Garcia Trillos Nicolas García Trillos OOD 37 10 0 13 Sep 2021
Distributionally Robust Learning Ruidi Chen I. Paschalidis OOD 25 65 0 20 Aug 2021
Algorithmic Bias and Data Bias: Understanding the Relation between Distributionally Robust Optimization and Data Curation Agnieszka Słowik Léon Bottou FaML 43 19 0 17 Jun 2021
Distributionally robust risk map for learning-based motion planning and control: A semidefinite programming approach A. Hakobyan Insoon Yang 104 25 0 03 May 2021
Unbalanced minibatch Optimal Transport; applications to Domain Adaptation Kilian Fatras Thibault Séjourné Nicolas Courty Rémi Flamary OT 34 146 0 05 Mar 2021
Adversarially Robust Kernel Smoothing Jia-Jie Zhu Christina Kouridi Yassine Nemmour Bernhard Schölkopf 26 7 0 16 Feb 2021
First-order Optimization for Superquantile-based Supervised Learning Yassine Laguel J. Malick Zaïd Harchaoui 12 9 0 30 Sep 2020
Distributionally Robust Losses for Latent Covariate Mixtures John C. Duchi Tatsunori Hashimoto Hongseok Namkoong 13 79 0 28 Jul 2020
A Distributionally Robust Approach to Fair Classification Bahar Taşkesen Viet Anh Nguyen Daniel Kuhn Jose H. Blanchet FaML 26 61 0 18 Jul 2020
A Stochastic Subgradient Method for Distributionally Robust Non-Convex Learning Mert Gurbuzbalaban A. Ruszczynski Landi Zhu 20 9 0 08 Jun 2020
Distributionally Robust Weighted $k$ -Nearest Neighbors Shixiang Zhu Liyan Xie Minghe Zhang Rui Gao Yao Xie OOD 21 7 0 07 Jun 2020
Adversarial Classification via Distributional Robustness with Wasserstein Ambiguity Nam Ho-Nguyen Stephen J. Wright OOD 40 16 0 28 May 2020
On Linear Optimization over Wasserstein Balls Man-Chung Yue Daniel Kuhn W. Wiesemann 9 50 0 15 Apr 2020
Posterior asymptotics in Wasserstein metrics on the real line Minwoo Chae P. De Blasi S. Walker 8 6 0 12 Mar 2020
Geometric Dataset Distances via Optimal Transport David Alvarez-Melis Nicolò Fusi OT 72 194 0 07 Feb 2020
Certifying Some Distributional Robustness with Principled Adversarial Training Aman Sinha Hongseok Namkoong Riccardo Volpi John C. Duchi OOD 38 854 0 29 Oct 2017
Limit laws of the empirical Wasserstein distance: Gaussian distributions Thomas Rippl Axel Munk A. Sturm 46 64 0 15 Jul 2015