Numerical Analysis of $\mathcal{V}\mathcal{U}$-Decomposition, $\mathcal{U}$-Gradient, and $\mathcal{U}$-Hessian Approximations

DOI10.1137/130933691zbMath1318.49053OpenAlexW2089331999MaRDI QIDQ5245370

W. Hare

Publication date: 8 April 2015

Published in: SIAM Journal on Optimization (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1137/130933691

zbMATH Keywords

convex optimizationderivative-free optimization\(\mathcal{VU}\)-decompositionmax-function\(\mathcal{U}\)-gradient\(\mathcal{U}\)-Hessian

Mathematics Subject Classification ID

Convex programming (90C25) Derivative-free methods and methods using generalized derivatives (90C56) Numerical optimization and variational techniques (65K10) Set-valued maps in general topology (54C60) Decomposition methods (49M27) Optimality conditions for minimax problems (49K35) Discrete approximations in optimal control (49M25)

Related Items (6)

Computing proximal points of convex functions with inexact subgradients ⋮ On partial smoothness, tilt stability and the \({\mathcal {VU}}\)-decomposition ⋮ The \(\mathcal{U}\)-Lagrangian, fast track, and partial smoothness of a prox-regular function ⋮ A derivative-free 𝒱𝒰-algorithm for convex finite-max problems ⋮ The chain rule for VU-decompositions of nonsmooth functions ⋮ Derivative-free optimization methods

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