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...

Celý popis

Podrobná bibliografia

Vydané v:	Set-valued and variational analysis Ročník 29; číslo 4; s. 967 - 996
Hlavní autori:	Laguel, Yassine, Pillutla, Krishna, Malick, Jérôme, Harchaoui, Zaid
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Dordrecht Springer Netherlands 01.12.2021 Springer Nature B.V Springer
Predmet:	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
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!