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Large-scale nonlinear programming algorithm using projection methods

100%

Białoń P.

Discussiones Mathematicae, Differential Inclusions, Control and Optimization

2000

tom 20

nr 2

171-194

A method for solving large convex optimization problems is presented. Such problems usually contain a big linear part and only a small or medium nonlinear part. The parts are tackled using two specialized (and thus efficient) external solvers: purely nonlinear and large-scale linear with a quadratic goal function. The decomposition uses an alteration of projection methods. The construction of the method is based on the zigzagging phenomenon and yields a non-asymptotic convergence, not dependent on a large dimension of the problem. The method preserves its convergence properties under limitations in complicating sets by geometric cuts. Various aspects and variants of the method are analyzed theoretically and experimentally.

A linear Support Vector Machine solver for a large number of training examples

38%

Białoń P.

Control and Cybernetics

2009

tom 38

nr 1

281-300

Ograniczanie wyników

1 Control and Cybernetics

1 Discussiones Mathematicae, Differential Inclusions, Control and Optimization

2 Białoń P.

1 2009

1 2000

Wyniki wyszukiwania

Large-scale nonlinear programming algorithm using projection methods

A linear Support Vector Machine solver for a large number of training examples