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| Ladislav Luksan and Jan Vlcek | ||||||||
| Key words: | ||||||||
| unconstrained optimization, large-scale optimization, nonsmooth optimization, bundle-type methods, variable metric methods, nonlinear least squares, partially separable problems, computational experiments | ||||||||
| Mathematices Subject Classification: 65K05 | ||||||||
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| Abstract: | |||
| In this contribution, we propose a new partitioned variable metric method for minimizing nonsmooth partially separable functions. After a short introduction, the complete algorithm is introduced and some implementation details are given. We prove that this algorithm is globally convergent under standard mild assumptions. Computational experiments given confirm efficiency and robustness of the new method. | |||
| Variable metric method for minimization of partially separable nonsmooth functions | |
| Special Issue on Conjugate Gradient and Quasi-Newton Methods for Nonlinear Optimization | |||
| Volume 2, Number 1, January 2006, pp. 59-70 | |||