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Data-driven Optimal Cost Selection for Distributionally Robust Optimization

19 May 2017

Papers citing "Data-driven Optimal Cost Selection for Distributionally Robust Optimization"

25 / 25 papers shown

Title
Data Heterogeneity Modeling for Trustworthy Machine Learning Jiashuo Liu Peng Cui 52 0 0 01 Jun 2025
DRO: A Python Library for Distributionally Robust Optimization in Machine Learning Jiashuo Liu Tianyu Wang Henry Lam Hongseok Namkoong Jose H. Blanchet AI4CE 44 1 0 29 May 2025
Mixed-feature Logistic Regression Robust to Distribution Shifts Qingshi Sun Nathan Justin A. Gómez P. Vayanos OOD 73 0 0 15 Mar 2025
LLM Embeddings Improve Test-time Adaptation to Tabular $Y\|X$ -Shifts Yibo Zeng Jiashuo Liu Henry Lam Hongseok Namkoong LMTD 98 2 0 09 Oct 2024
Geometry-Calibrated DRO: Combating Over-Pessimism with Free Energy Implications Jiashuo Liu Jiayun Wu Tianyu Wang Hao Zou Yue Liu Peng Cui 62 4 0 08 Nov 2023
Dr. FERMI: A Stochastic Distributionally Robust Fair Empirical Risk Minimization Framework Sina Baharlouei Meisam Razaviyayn FaML OOD 85 0 0 20 Sep 2023
The out-of-sample prediction error of the square-root-LASSO and related estimators J. M. Olea Cynthia Rush Amilcar Velez J. Wiesel OOD 92 6 0 14 Nov 2022
Wasserstein Distributionally Robust Optimization with Wasserstein Barycenters Tim Tsz-Kit Lau Han Liu OOD 91 2 0 23 Mar 2022
Human Imperceptible Attacks and Applications to Improve Fairness Xinru Hua Huanzhong Xu Jose H. Blanchet V. Nguyen AAML 69 3 0 30 Nov 2021
Distributionally Robust Semi-Supervised Learning Over Graphs A. Sadeghi Meng Ma Bingcong Li G. Giannakis OOD 102 13 0 20 Oct 2021
Towards Out-Of-Distribution Generalization: A Survey Jiashuo Liu Zheyan Shen Yue He Xingxuan Zhang Renzhe Xu Han Yu Peng Cui CML OOD 168 536 0 31 Aug 2021
Distributionally Robust Learning Ruidi Chen I. Paschalidis OOD 93 69 0 20 Aug 2021
Statistical Analysis of Wasserstein Distributionally Robust Estimators Jose H. Blanchet Karthyek Murthy Viet Anh Nguyen 67 48 0 04 Aug 2021
Towards a Theoretical Framework of Out-of-Distribution Generalization Haotian Ye Chuanlong Xie Tianle Cai Ruichen Li Zhenguo Li Liwei Wang OODD OOD 136 112 0 08 Jun 2021
Wasserstein Distributionally Robust Optimization: Theory and Applications in Machine Learning Daniel Kuhn Peyman Mohajerin Esfahani Viet Anh Nguyen Soroosh Shafieezadeh-Abadeh OOD 66 397 0 23 Aug 2019
Distributionally Robust Optimization: A Review Hamed Rahimian Sanjay Mehrotra 74 134 0 13 Aug 2019
Confidence Regions in Wasserstein Distributionally Robust Estimation Jose H. Blanchet Karthyek Murthy Nian Si OOD 83 57 0 04 Jun 2019
Distributionally Robust Optimization and Generalization in Kernel Methods Matthew Staib Stefanie Jegelka 93 134 0 27 May 2019
A Distributionally Robust Boosting Algorithm Jose H. Blanchet Yang Kang Fan Zhang Zhangyi Hu 47 7 0 20 May 2019
Lipschitz Networks and Distributional Robustness Zac Cranko Simon Kornblith Zhan Shi Richard Nock OOD 63 11 0 04 Sep 2018
Calibration of Distributionally Robust Empirical Optimization Models Jun-ya Gotoh M. J. Kim Andrew E. B. Lim 96 44 0 17 Nov 2017
Certifying Some Distributional Robustness with Principled Adversarial Training Aman Sinha Hongseok Namkoong Riccardo Volpi John C. Duchi OOD 145 866 0 29 Oct 2017
Regularization via Mass Transportation Soroosh Shafieezadeh-Abadeh Daniel Kuhn Peyman Mohajerin Esfahani OOD 138 206 0 27 Oct 2017
Doubly Robust Data-Driven Distributionally Robust Optimization Jose H. Blanchet Yang Kang Fan Zhang Fei He Zhangyi Hu OOD 82 13 0 19 May 2017
Sample Out-Of-Sample Inference Based on Wasserstein Distance Jose H. Blanchet Yang Kang 99 35 0 04 May 2016