Форма представления | Статьи в зарубежных журналах и сборниках |
Год публикации | 2019 |
Язык | английский |
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Габидуллина Зульфия Равилевна, автор
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Библиографическое описание на языке оригинала |
Gabidullina Z.R., Adaptive Conditional Gradient Method//Journal of Optimization Theory and Applications. - 2019. - Vol.183, Is.3. - P.1077-1098. |
Аннотация |
We present a novel fully adaptive conditional gradient method with the step length regulation for solving pseudo-convex constrained optimization problems. We propose some deterministic rules of the step length regulation in a normalized direction. These rules guarantee to find the step length by utilizing the finite procedures and provide the strict relaxation of the objective function at each iteration. We prove that the sequence of the function values for the iterates generated by the algorithm converges globally to the objective function optimal value with sublinear rate. |
Ключевые слова |
Optimization problems, Pseudo-convex function, Adaptation, Descent direction, Normalization, Step length Regulation, Rate of convergence. |
Название журнала |
Journal of Optimization Theory and Applications
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URL |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85074016312&doi=10.1007%2fs10957-019-01585-w&partnerID=40&md5=61f69fdf521f5d9717001747d2b37c40 |
Пожалуйста, используйте этот идентификатор, чтобы цитировать или ссылаться на эту карточку |
https://repository.kpfu.ru/?p_id=215227 |
Полная запись метаданных |
Поле DC |
Значение |
Язык |
dc.contributor.author |
Габидуллина Зульфия Равилевна |
ru_RU |
dc.date.accessioned |
2019-01-01T00:00:00Z |
ru_RU |
dc.date.available |
2019-01-01T00:00:00Z |
ru_RU |
dc.date.issued |
2019 |
ru_RU |
dc.identifier.citation |
Gabidullina Z.R., Adaptive Conditional Gradient Method//Journal of Optimization Theory and Applications. - 2019. - Vol.183, Is.3. - P.1077-1098. |
ru_RU |
dc.identifier.uri |
https://repository.kpfu.ru/?p_id=215227 |
ru_RU |
dc.description.abstract |
Journal of Optimization Theory and Applications |
ru_RU |
dc.description.abstract |
We present a novel fully adaptive conditional gradient method with the step length regulation for solving pseudo-convex constrained optimization problems. We propose some deterministic rules of the step length regulation in a normalized direction. These rules guarantee to find the step length by utilizing the finite procedures and provide the strict relaxation of the objective function at each iteration. We prove that the sequence of the function values for the iterates generated by the algorithm converges globally to the objective function optimal value with sublinear rate. |
ru_RU |
dc.language.iso |
ru |
ru_RU |
dc.subject |
Optimization problems |
ru_RU |
dc.subject |
Pseudo-convex function |
ru_RU |
dc.subject |
Adaptation |
ru_RU |
dc.subject |
Descent direction |
ru_RU |
dc.subject |
Normalization |
ru_RU |
dc.subject |
Step length Regulation |
ru_RU |
dc.subject |
Rate of convergence. |
ru_RU |
dc.title |
Adaptive Conditional Gradient Method |
ru_RU |
dc.type |
Статьи в зарубежных журналах и сборниках |
ru_RU |
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