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Rui Gao
Rui Gao
Assistant Professor, University of Texas at Austin
Bestätigte E-Mail-Adresse bei mccombs.utexas.edu - Startseite
Titel
Zitiert von
Zitiert von
Jahr
Distributionally robust stochastic optimization with Wasserstein distance
R Gao, A Kleywegt
Mathematics of Operations Research, 2016
880*2016
Wasserstein distributionally robust optimization and variation regularization
R Gao, X Chen, AJ Kleywegt
Operations Research, 2017
261*2017
Risk-based distributionally robust optimal gas-power flow with wasserstein distance
C Wang, R Gao, W Wei, M Shafie-khah, T Bi, JPS Catalao
IEEE Transactions on Power Systems 34 (3), 2190-2204, 2019
1172019
Risk-based distributionally robust optimal power flow with dynamic line rating
C Wang, R Gao, F Qiu, J Wang, L Xin
IEEE Transactions on Power Systems 33 (6), 6074-6086, 2018
1122018
Finite-sample guarantees for Wasserstein distributionally robust optimization: Breaking the curse of dimensionality
R Gao
Operations Research 71 (6), 2291-2306, 2023
1062023
Robust hypothesis testing using Wasserstein uncertainty sets
R Gao, L Xie, Y Xie, H Xu
Advances in Neural Information Processing Systems 31, 2018
862018
Distributionally robust stochastic optimization with dependence structure
R Gao, AJ Kleywegt
arXiv preprint arXiv:1701.04200, 2017
552017
Sinkhorn distributionally robust optimization
J Wang, R Gao, Y Xie
arXiv preprint arXiv:2109.11926, 2021
442021
Optimal robust policy for feature-based newsvendor
L Zhang, J Yang, R Gao
Management Science, 2023
34*2023
Two-sample test using projected wasserstein distance
J Wang, R Gao, Y Xie
2021 IEEE International Symposium on Information Theory (ISIT), 3320-3325, 2021
302021
Analyzing the generalization capability of SGLD using properties of Gaussian channels
H Wang, Y Huang, R Gao, F Calmon
Advances in Neural Information Processing Systems 34, 24222-24234, 2021
292021
A short and general duality proof for Wasserstein distributionally robust optimization
L Zhang, J Yang, R Gao
Operations Research, 2024
19*2024
Reliable off-policy evaluation for reinforcement learning
J Wang, R Gao, H Zha
Operations Research 72 (2), 699-716, 2024
182024
Generalization bounds for noisy iterative algorithms using properties of additive noise channels
H Wang, R Gao, FP Calmon
Journal of machine learning research 24 (26), 1-43, 2023
182023
Data-driven robust optimization with known marginal distributions
R Gao, AJ Kleywegt
Working paper, 2017
182017
Two-sample Test with Kernel Projected Wasserstein Distance
J Wang, R Gao, Y Xie
arXiv preprint arXiv:2102.06449, 2021
172021
Aleatoric and epistemic discrimination: Fundamental limits of fairness interventions
H Wang, L He, R Gao, F Calmon
Advances in Neural Information Processing Systems 36, 2024
162024
Contextual decision-making under parametric uncertainty and data-driven optimistic optimization
J Cao, R Gao
Available at Optimization Online, 2021
152021
Decision-making with Side Information: A Causal Transport Robust Approach
J Yang, L Zhang, N Chen, R Gao, M Hu
142022
Generalization bounds for (Wasserstein) robust optimization
Y An, R Gao
Advances in Neural Information Processing Systems 34, 10382-10392, 2021
142021
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