Jan 4, 2022 · Our paper addresses stability of optimization problems using composite risk functionals which are subjected to measure perturbations. Our main ...
Jun 28, 2022 · Our goals are to extend the theory of stability of stochastic optimization problems with respect to measure perturbation to the case of ...
[PDF] Stability and Sample-based Approximations of Composite ...
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May 23, 2022 · Penev, “Stability and Sample-based. Approximations of Composite Stochastic Optimization Problems,” to appear in Operations Research (2022). 2 ...
Sep 1, 2023 · The paper addresses the stability of the decision problems when the composite risk functionals are subjected to measure perturbations at ...
The paper addresses the stability of the decision problems when the composite risk functionals are subjected to measure perturbations at multiple levels of ...
In this paper, we analyzed general approximations of stochastic composite optimization problems when the probability measure of the random data is subject ...
Jan 4, 2022 · We have shown that the new formulations provide less biased estimation of the optimal value under certain assumptions while the standard error ...
Jan 4, 2022 · Our main focus is the asymptotic behavior of data-driven formulations with empirical or smoothing estimators such as kernels or wavelets applied ...
D Dentcheva, Y Lin, S Penev, Stability and sample-based approximations of composite stochastic optimization problems, Operations Research 71 (5), (2022) 1871- ...
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2022, Stability and Sample-based Approximations of Composite Stochastic Optimization ... Composite Risk Functionals and Risk Optimization Problems. Hall P ...