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A proximal bundle method based on approximate subgradients

journal contribution
posted on 2023-06-07, 20:32 authored by Michael Hintermueller
In this paper a proximal bundle method is introduced that is capable to deal with approximate subgradients. No further knowledge of the approximation quality (like explicit knowledge or controllability of error bounds) is required for proving convergence. It is shown that every accumulation point of the sequence of iterates generated by the proposed algorithm is a well-defined approximate solution of the exact minimization problem. In the case of exact subgradients the algorithm behaves like well-established proximal bundle methods. Numerical tests emphasize the theoretical findings.

History

Publication status

  • Published

Journal

Computational Optimization and Applications

ISSN

0926-6003

Publisher

Springer Verlag

Issue

3

Volume

20

Page range

245-266

Department affiliated with

  • Mathematics Publications

Full text available

  • No

Peer reviewed?

  • Yes

Legacy Posted Date

2012-02-06

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