Inexact Accelerated Proximal Gradient Algorithms For Matrix l_{2,1}-Norm Minimization Problem in Multi-Task Feature Learning | Zendy

Yaping Hu | Zendy; Zengxin Wei | Zendy; Gonglin Yuan | Zendy

Open Access

Inexact Accelerated Proximal Gradient Algorithms For Matrix l_{2,1}-Norm Minimization Problem in Multi-Task Feature Learning

Author(s) -

Yaping Hu,

Zengxin Wei,

Gonglin Yuan

Publication year - 2014

Publication title -

statistics optimization and information computing

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.297

H-Index - 12

eISSN - 2311-004X

pISSN - 2310-5070

DOI - 10.19139/106

Subject(s) - hessian matrix , lipschitz continuity , eigenvalues and eigenvectors , matrix (chemical analysis) , norm (philosophy) , algorithm , minification , convergence (economics) , computer science , feature (linguistics) , mathematics , constant (computer programming) , mathematical optimization , mathematical analysis , linguistics , philosophy , physics , materials science , quantum mechanics , political science , law , economics , composite material , economic growth , programming language

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