Generalized sequential differential calculus for expected-integral functionals
BS Mordukhovich, P Pérez-Aros - Set-Valued and Variational Analysis, 2021 - Springer
Set-Valued and Variational Analysis, 2021•Springer
Motivated by applications to stochastic programming, we introduce and study the expected-
integral functionals, which are mappings given in an integral form depending on two
variables, the first a finite dimensional decision vector and the second one an integrable
function. The main goal of this paper is to establish sequential versions of Leibniz's rule for
regular subgradients by employing and developing appropriate tools of variational analysis.
integral functionals, which are mappings given in an integral form depending on two
variables, the first a finite dimensional decision vector and the second one an integrable
function. The main goal of this paper is to establish sequential versions of Leibniz's rule for
regular subgradients by employing and developing appropriate tools of variational analysis.
Abstract
Motivated by applications to stochastic programming, we introduce and study the expected-integral functionals, which are mappings given in an integral form depending on two variables, the first a finite dimensional decision vector and the second one an integrable function. The main goal of this paper is to establish sequential versions of Leibniz’s rule for regular subgradients by employing and developing appropriate tools of variational analysis.
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