Numerical Structure of the Hessian of the Lagrange Dual Function for a Class of Convex Problems

DOI10.1137/15M1024573zbMath1394.90458OpenAlexW2594682504MaRDI QIDQ2968548

Emil Klintberg, Sébastien Gros

Publication date: 17 March 2017

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

Full work available at URL: https://doi.org/10.1137/15m1024573

zbMATH Keywords

Newton methoddual decompositionstructure exploitationdual Hessian

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Convex programming (90C25) Numerical methods involving duality (49M29) Newton-type methods (49M15) Methods of quasi-Newton type (90C53) Decomposition methods (49M27) Numerical methods of relaxation type (49M20)

Uses Software

• qpDUNES
• CSparse

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• A parallel quadratic programming method for dynamic optimization problems
• Interior-point Lagrangian decomposition method for separable convex optimization
• Bounds for the entries of matrix functions with applications to preconditioning
• Rate Analysis of Inexact Dual First-Order Methods Application to Dual Decomposition
• Dual Ascent Methods for Problems with Strictly Convex Costs and Linear Constraints: A Unified Approach
• Direct Methods for Sparse Linear Systems
• Decay Rates for Inverses of Band Matrices
• A lagrangean relaxation algorithm for the constrained matrix problem
• Decay Properties of Spectral Projectors with Applications to Electronic Structure
• Constrained Consensus and Optimization in Multi-Agent Networks
• An Inexact Perturbed Path-Following Method for Lagrangian Decomposition in Large-Scale Separable Convex Optimization
• Faster and Simpler Algorithms for Multicommodity Flow and Other Fractional Packing Problems

This page was built for publication: Numerical Structure of the Hessian of the Lagrange Dual Function for a Class of Convex Problems