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Rui Gao
Rui Gao
Assistant Professor, University of Texas at Austin
Verified email at mccombs.utexas.edu - Homepage
Title
Cited by
Cited by
Year
Distributionally robust stochastic optimization with Wasserstein distance
R Gao, A Kleywegt
Mathematics of Operations Research, 2016
751*2016
Wasserstein distributionally robust optimization and variation regularization
R Gao, X Chen, AJ Kleywegt
Operations Research, 2017
222*2017
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
992018
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
932019
Finite-sample guarantees for Wasserstein distributionally robust optimization: Breaking the curse of dimensionality
R Gao
Operations Research 71 (6), 2291-2306, 2023
792023
Robust hypothesis testing using Wasserstein uncertainty sets
R Gao, L Xie, Y Xie, H Xu
Advances in Neural Information Processing Systems 31, 2018
742018
Distributionally robust stochastic optimization with dependence structure
R Gao, AJ Kleywegt
arXiv preprint arXiv:1701.04200, 2017
532017
Sinkhorn distributionally robust optimization
J Wang, R Gao, Y Xie
arXiv preprint arXiv:2109.11926, 2021
292021
Two-sample test using projected wasserstein distance
J Wang, R Gao, Y Xie
2021 IEEE International Symposium on Information Theory (ISIT), 3320-3325, 2021
242021
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
222021
Optimal robust policy for feature-based newsvendor
L Zhang, J Yang, R Gao
Management Science, 2023
18*2023
Data-driven robust optimization with known marginal distributions
R Gao, AJ Kleywegt
Working paper, 2017
182017
Reliable off-policy evaluation for reinforcement learning
J Wang, R Gao, H Zha
Operations Research 72 (2), 699-716, 2024
152024
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
152023
Generalization bounds for (Wasserstein) robust optimization
Y An, R Gao
Advances in Neural Information Processing Systems 34, 10382-10392, 2021
142021
Two-sample Test with Kernel Projected Wasserstein Distance
J Wang, R Gao, Y Xie
arXiv preprint arXiv:2102.06449, 2021
132021
Contextual decision-making under parametric uncertainty and data-driven optimistic optimization
J Cao, R Gao
Available at Optimization Online, 2021
132021
A simple and general duality proof for Wasserstein distributionally robust optimization
L Zhang, J Yang, R Gao
arXiv preprint arXiv:2205.00362, 2022
122022
Robust hypothesis testing with wasserstein uncertainty sets
L Xie, R Gao, Y Xie
arXiv preprint arXiv:2105.14348, 2021
82021
Bridging explicit and implicit deep generative models via neural stein estimators
Q Wu, R Gao, H Zha
Advances in Neural Information Processing Systems 34, 11274-11286, 2021
6*2021
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