Parallel and distributed sparse optimization

This paper proposes parallel and distributed algorithms for solving very large-scale sparse optimization problems on computer clusters and clouds. Modern datasets usually have a large number of features or training samples, and they are usually stored in a distributed manner. Motivated by the need o...

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Veröffentlicht in:	Conference record - Asilomar Conference on Signals, Systems, & Computers S. 659 - 646
Hauptverfasser:	Peng, Zhimin, Yan, Ming, Yin, Wotao
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 01.11.2013
Schlagworte:	Broadcasting Clustering algorithms Convergence Distributed databases GRock l 1 minimization LASSO Logistics Optimization parallel and distributed computing sparse optimization Vectors
ISSN:	1058-6393
Online-Zugang:	Volltext
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