A conjugate gradient method for the unconstrained minimization of strictly convex quadratic splines

DOI10.1007/BF02592329zbMath0851.90088MaRDI QIDQ1919811

Wu Li

Publication date: 28 July 1996

Published in: Mathematical Programming. Series A. Series B (Search for Journal in Brave)

zbMATH Keywords

conjugate gradient methodunconstrained minimizationfinite convergenceglobal error estimatespiecewise linear equationsstrictly convex quadratic spline

Mathematics Subject Classification ID

Convex programming (90C25) Quadratic programming (90C20)

Related Items (3)

Mathematical programming formulations for piecewise polynomial functions ⋮ Regularized gap function as penalty term for constrained minimization problems ⋮ Linear Convergence of Descent Methods for the Unconstrained Minimization of Restricted Strongly Convex Functions

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• An O(n) algorithm for quadratic knapsack problems
• An algorithm for a singly constrained class of quadratic programs subject upper and lower bounds
• A generalized conjugate gradient algorithm for solving a class of quadratic programming problems
• A class of methods for solving large, convex quadratic programs subject to box constraints
• Global convergence result for conjugate gradient methods
• Gauss-Seidel method for least-distance problems
• Linearly convergent descent methods for the unconstrained minimization of convex quadratic splines
• Efficient generalized conjugate gradient algorithms. II: Implementation
• Iterative Methods for Large Convex Quadratic Programs: A Survey
• A Newton Method for Convex Regression, Data Smoothing, and Quadratic Programming with Bounded Constraints
• Descent Property and Global Convergence of the Fletcher—Reeves Method with Inexact Line Search
• Quasi-Newton Updates with Bounds
• On the Solution of Large Quadratic Programming Problems with Bound Constraints
• The solution of a quadratic programming problem using fast methods to solve systems of linear equations
• Some convergence properties of the conjugate gradient method
• Restart procedures for the conjugate gradient method
• On the Maximization of a Concave Quadratic Function with Box Constraints
• A New Algorithm for Solving Strictly Convex Quadratic Programs
• Error Bounds for Piecewise Convex Quadratic Programs and Applications
• Function minimization by conjugate gradients
• The conjugate gradient method in extremal problems

This page was built for publication: A conjugate gradient method for the unconstrained minimization of strictly convex quadratic splines