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• W2014405554 abstract "We reformulate convex quadratic programs with simple bound constraints and strictly convex quadratic programs as problems of unconstrained minimization of convex quadratic splines. Therefore, any algorithm for finding a minimizer of a convex quadratic spline can be used to solve these quadratic programming problems. In this paper, we propose a Newton method to find a minimizer of a convex quadratic spline derived from the unconstrained reformulation of a strictly convex quadratic programming problem. The Newton method is a natural mixture of a descent method and an active-set method. Moreover, it is an iterative method, yet it terminates in finite operations (in exact arithmetic)." @default.
• W2014405554 created "2016-06-24" @default.
• W2014405554 creator A5000060963 @default.
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• W2014405554 date "1997-08-01" @default.
• W2014405554 modified "2023-10-16" @default.
• W2014405554 title "A New Algorithm for Solving Strictly Convex Quadratic Programs" @default.
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• W2014405554 doi "https://doi.org/10.1137/s1052623493246045" @default.
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