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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Bibliographic Details

Published in:	Conference record - Asilomar Conference on Signals, Systems, & Computers pp. 659 - 646
Main Authors:	Peng, Zhimin, Yan, Ming, Yin, Wotao
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01.11.2013
Subjects:	Broadcasting Clustering algorithms Convergence Distributed databases GRock l 1 minimization LASSO Logistics Optimization parallel and distributed computing sparse optimization Vectors
ISSN:	1058-6393
Online Access:	Get full text
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