Superquantiles at Work: Machine Learning Applications and Efficient Subgradient Computation

R. Tyrell Rockafellar and his collaborators introduced, in a series of works, new regression modeling methods based on the notion of superquantile (or conditional value-at-risk). These methods have been influential in economics, finance, management science, and operations research in general. Recent...

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Bibliographic Details

Published in:	Set-valued and variational analysis Vol. 29; no. 4; pp. 967 - 996
Main Authors:	Laguel, Yassine, Pillutla, Krishna, Malick, Jérôme, Harchaoui, Zaid
Format:	Journal Article
Language:	English
Published:	Dordrecht Springer Netherlands 01.12.2021 Springer Nature B.V Springer
Subjects:	Algorithms Analysis Convex and Variational Analysis Machine learning Mathematics Mathematics and Statistics Operations research Optimization Optimization and Control Robustness (mathematics) SI: Optimization Robust optimization Superquantiles Smoothing Machine learning
ISSN:	1877-0533, 1877-0541
Online Access:	Get full text
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