An Affine-Scaling Interior-Point Method for Continuous Knapsack Constraints with Application to Support Vector Machines

DOI10.1137/090766255zbMath1218.90114OpenAlexW2002567709MaRDI QIDQ3004989

Hongchao Zhang, William W. Hager, María D. González-Lima

Publication date: 6 June 2011

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

Full work available at URL: https://semanticscholar.org/paper/28376a61f6df97bcb877be1c680afd76aef0cb52

zbMATH Keywords

global convergencelinear convergencesupport vector machinesinterior-pointaffine-scalingcyclic Barzilai-Borwein methods

Mathematics Subject Classification ID

Large-scale problems in mathematical programming (90C06) Nonconvex programming, global optimization (90C26) Complexity and performance of numerical algorithms (65Y20)

Related Items (11)

An augmented Lagrangian affine scaling method for nonlinear programming ⋮ A wide neighborhood arc-search interior-point algorithm for convex quadratic programming with box constraints and linear constraints ⋮ Margin maximization in spherical separation ⋮ A Reduced-Space Algorithm for Minimizing $\ell_1$-Regularized Convex Functions ⋮ A Newton's method for the continuous quadratic knapsack problem ⋮ Simple solution methods for separable mixed linear and quadratic knapsack problem ⋮ A Two-Phase Gradient Method for Quadratic Programming Problems with a Single Linear Constraint and Bounds on the Variables ⋮ Parallel decomposition methods for linearly constrained problems subject to simple bound with application to the SVMs training ⋮ An affine scaling method for optimization problems with polyhedral constraints ⋮ Generalized affine scaling algorithms for linear programming problems ⋮ Nearest neighbors methods for support vector machines

Uses Software

• GPDT

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