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Data-driven Optimal Cost Selection for Distributionally Robust
  Optimization
v1v2v3 (latest)

Data-driven Optimal Cost Selection for Distributionally Robust Optimization

19 May 2017
Jose H. Blanchet
Yang Kang
Fan Zhang
Karthyek Murthy
    OOD
ArXiv (abs)PDFHTML

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

25 / 25 papers shown
Title
Data Heterogeneity Modeling for Trustworthy Machine Learning
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
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
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
LLM Embeddings Improve Test-time Adaptation to Tabular Y∣XY|XY∣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
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
Dr. FERMI: A Stochastic Distributionally Robust Fair Empirical Risk Minimization Framework
Sina Baharlouei
Meisam Razaviyayn
FaMLOOD
85
0
0
20 Sep 2023
The out-of-sample prediction error of the square-root-LASSO and related
  estimators
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
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
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
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
Towards Out-Of-Distribution Generalization: A Survey
Jiashuo Liu
Zheyan Shen
Yue He
Xingxuan Zhang
Renzhe Xu
Han Yu
Peng Cui
CMLOOD
168
536
0
31 Aug 2021
Distributionally Robust Learning
Distributionally Robust Learning
Ruidi Chen
I. Paschalidis
OOD
93
69
0
20 Aug 2021
Statistical Analysis of Wasserstein Distributionally Robust Estimators
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
Towards a Theoretical Framework of Out-of-Distribution Generalization
Haotian Ye
Chuanlong Xie
Tianle Cai
Ruichen Li
Zhenguo Li
Liwei Wang
OODDOOD
136
112
0
08 Jun 2021
Wasserstein Distributionally Robust Optimization: Theory and
  Applications in Machine Learning
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
Distributionally Robust Optimization: A Review
Hamed Rahimian
Sanjay Mehrotra
74
134
0
13 Aug 2019
Confidence Regions in Wasserstein Distributionally Robust Estimation
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
Distributionally Robust Optimization and Generalization in Kernel Methods
Matthew Staib
Stefanie Jegelka
93
134
0
27 May 2019
A Distributionally Robust Boosting Algorithm
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
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
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
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
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
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
Sample Out-Of-Sample Inference Based on Wasserstein Distance
Jose H. Blanchet
Yang Kang
99
35
0
04 May 2016
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