NOISY MATRIX COMPLETION: UNDERSTANDING STATISTICAL GUARANTEES FOR CONVEX RELAXATION VIA NONCONVEX OPTIMIZATION.

Chen, Yuxin; Chi, Yuejie; Fan, Jianqing; Ma, Cong; Yan, Yuling

Chen, Yuxin; Chi, Yuejie; Fan, Jianqing; Ma, Cong; Yan, Yuling.

Afiliación

Chen Y; Department of Electrical Engineering, Princeton University, Princeton, NJ 08544, USA.
Chi Y; Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA.
Fan J; Department of Operations Research and Financial Engineering, Princeton University, Princeton, NJ 08544, USA.
Ma C; Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA.
Yan Y; Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA.

SIAM J Optim ; 30(4): 3098-3121, 2020.

Article en En | MEDLINE | ID: mdl-34305368

Palabras clave

90C25; 90C26; BurerMonteiro approach; convex relaxation; matrix completion; minimaxity; nonconvex optimization; stability

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: SIAM J Optim Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos

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