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Adaptive cubic regularisation methods for unconstrained optimization. Part II: worst-case function- and derivative-evaluation complexity.

Abstract:

An Adaptive Regularisation framework using Cubics (ARC) was proposed for unconstrained optimization and analysed in Cartis, Gould and Toint (Part I, Math Program, doi: 10.1007/s10107-009-0286-5, 2009), generalizing at the same time an unpublished method due to Griewank (Technical Report NA/12, 1981, DAMTP, University of Cambridge), an algorithm by Nesterov and Polyak (Math Program 108(1):177-205, 2006) and a proposal by Weiser, Deuflhard and Erdmann (Optim Methods Softw 22(3):413-431, 2007). ...

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Publication status:
Published

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Publisher copy:
10.1007/s10107-009-0337-y

Authors


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Institution:
University of Oxford
Department:
Oxford, MPLS, Mathematical Inst
Gould, NIM More by this author
Journal:
Math. Program.
Volume:
130
Issue:
2
Pages:
295-319
Publication date:
2011
DOI:
EISSN:
1436-4646
ISSN:
0025-5610
URN:
uuid:32610f29-f8a6-4930-90e6-cdf5b522db07
Source identifiers:
400611
Local pid:
pubs:400611

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