Gradients and Subgradients of Buffered Failure Probability
Optimization and Control
2021-10-26 v2 Machine Learning
Abstract
Gradients and subgradients are central to optimization and sensitivity analysis of buffered failure probabilities. We furnish a characterization of subgradients based on subdifferential calculus in the case of finite probability distributions and, under additional assumptions, also a gradient expression for general distributions. Several examples illustrate the application of the results, especially in the context of optimality conditions.
Keywords
Cite
@article{arxiv.2109.05391,
title = {Gradients and Subgradients of Buffered Failure Probability},
author = {Johannes O. Royset and Ji-Eun Byun},
journal= {arXiv preprint arXiv:2109.05391},
year = {2021}
}