KFU. Card publication. Simplified versions of the conditional gradient method

KAZAN
FEDERAL UNIVERSITY

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- 中文
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SIMPLIFIED VERSIONS OF THE CONDITIONAL GRADIENT METHOD

Form of presentation

Articles in international journals and collections

Year of publication

2018

Язык

английский

Authors, employees of KFU

Konnov Igor Vasilevich, author

Bibliographic description in the original language

Konnov I.V., Simplified versions of the conditional gradient method//Optimization. - 2018. - Vol.67, Is.12. -P.2275-2290.

Annotation

We suggest simple modifications of the conditional gradient method for smooth optimization problems, which maintain the basic convergence properties, but reduce the implementation cost of each iteration essentially. Namely, we propose an adaptive step-size procedure without any line-search and inexact solution of the direction finding subproblem. Preliminary results of computational tests confirm efficiency of the proposed modifications.

Keywords

Optimization, conditional gradient method

The name of the journal

OPTIMIZATION

URL

https://www.tandfonline.com/doi/10.1080/02331934.2018.1530235

Please use this ID to quote from or refer to the card

https://repository.kpfu.ru/eng/?p_id=187886&p_lang=2

Full metadata record

Field DC	Value	Language
dc.contributor.author	Konnov Igor Vasilevich	ru_RU
dc.date.accessioned	2018-01-01T00:00:00Z	ru_RU
dc.date.available	2018-01-01T00:00:00Z	ru_RU
dc.date.issued	2018	ru_RU
dc.identifier.citation	Konnov I.V., Simplified versions of the conditional gradient method//Optimization. - 2018. - Vol.67, Is.12. -P.2275-2290.	ru_RU
dc.identifier.uri	https://repository.kpfu.ru/eng/?p_id=187886&p_lang=2	ru_RU
dc.description.abstract	OPTIMIZATION	ru_RU
dc.description.abstract	We suggest simple modifications of the conditional gradient method for smooth optimization problems, which maintain the basic convergence properties, but reduce the implementation cost of each iteration essentially. Namely, we propose an adaptive step-size procedure without any line-search and inexact solution of the direction finding subproblem. Preliminary results of computational tests confirm efficiency of the proposed modifications.	ru_RU
dc.language.iso	ru	ru_RU
dc.subject	Optimization	ru_RU
dc.subject	conditional gradient method	ru_RU
dc.title	Simplified versions of the conditional gradient method	ru_RU
dc.type	Articles in international journals and collections	ru_RU