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Implementable tensor methods in unconstrained convex optimization

In this paper we develop new tensor methods for unconstrained convex optimization, which solve at each iteration an auxiliary problem of minimizing convex multivariate polynomial. We analyze the simplest scheme, based on minimization of a regularized local model of the objective function, and its ac...

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Detalles Bibliográficos
Autor principal: Nesterov, Yurii
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7875858/
https://www.ncbi.nlm.nih.gov/pubmed/33627889
http://dx.doi.org/10.1007/s10107-019-01449-1

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