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Dropout training is distributionally robust optimal
J. Mach. Learn. Res., 2023Summary: This paper shows that dropout training in generalized linear models is the minimax solution of a two-player, zero-sum game where an adversarial nature corrupts a statistician's covariates using a multiplicative nonparametric errors-in-variables model.
Jose H. Blanchet +4 more
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Distributionally Robust Optimization under Distorted Expectations
SSRN Electronic Journal, 2020Optimal Decision Making Under Distorted Expectation with Partial Distribution Information Decision makers who are not risk neutral may evaluate expected values by distorting objective probabilities to reflect their risk attitudes, a phenomenon known as distorted expectations. This concept is widely applied in behavioral economics, insurance, finance,
Jun Cai +2 more
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An Approximation Scheme for Distributionally Robust Nonlinear Optimization
SIAM Journal on Optimization, 2020zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Johannes Milz, Michael Ulbrich
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Distributionally robust Optimal Control and MDP modeling
Operations Research Letters, 2021zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Distributionally Robust Stochastic Optimization with Wasserstein Distance
Mathematics of Operations Research, 2023Anton Kleywegt, Rui Gao
exaly
Target-based distributionally robust optimization for single machine scheduling
European Journal of Operational Research, 2022Qingwei Jin, Zhi Pei, Lianmin Zhang
exaly
Distributionally Robust Optimization with Data Geometry
Advances in Neural Information Processing Systems 35, 2022Jiashuo Liu +3 more
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