- Title
- Aggregate subgradient smoothing mehtods for large scale nonsmooth nonconvex optimisation and applications
- Creator
- Sultanova, Nargiz
- Date
- 2015
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/89653
- Identifier
- vital:9300
- Identifier
-
https://doi.org/10.1017/S0004972715000143
- Identifier
- ISSN:0004-9727
- Abstract
- Nonsmooth optimisation problems are problems which deal with minimisation or maximisation of functions that are not necessarily differentiable. They arise frequently in many practical applications, for example in engineering, machine learning and economics. In addition, some smooth problems can be reformulated as nonsmooth optimisation problems with a simpler structure or a smaller dimension. Despite the fact that there exist many algorithms for solving nonsmooth optimisation problems, the field is still very much in development. Nonsmooth nonconvex optimisation, in particular, is far from being considered a mature branch of optimisation.
- Publisher
- Cambridge University Press
- Relation
- Bulletin of the Australian Mathematical Society Vol. 91, no. 3 (2015), p. 523-524
- Rights
- Copyright © 2015 Australian Mathematical Publishing Association Inc
- Rights
- This metadata is freely available under a CCO license
- Subject
- 0101 Pure Mathematics; Large-scale problems; Mathematical programming; Nonsmooth optimisation
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