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Mathematics > Optimization and Control

arXiv:2109.05391 (math)
[Submitted on 12 Sep 2021 (v1), last revised 22 Oct 2021 (this version, v2)]

Title:Gradients and Subgradients of Buffered Failure Probability

Authors:Johannes O. Royset, Ji-Eun Byun
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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.
Subjects: Optimization and Control (math.OC); Machine Learning (cs.LG)
Cite as: arXiv:2109.05391 [math.OC]
  (or arXiv:2109.05391v2 [math.OC] for this version)
  https://doi.org/10.48550/arXiv.2109.05391

Submission history

From: Johannes Royset [view email]
[v1] Sun, 12 Sep 2021 00:04:24 UTC (441 KB)
[v2] Fri, 22 Oct 2021 20:33:56 UTC (681 KB)
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