Distributed proximal-gradient methods for convex optimization with inequality constraints

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Distributed proximal-gradient methods for convex optimization with inequality constraints

We consider a distributed optimization problem over a multi-agent network, in which the sum of several local convex objective functions is minimized subject to global convex inequality constraints. We first transform the constrained optimization problem to an unconstrained one, using the exact penal...

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Bibliographic Details
Main Authors:	Li, J., Wu, Changzhi, Wu, Z., Long, Q., Wang, Xiangyu
Format:	Journal Article
Published:	Australian Mathematical Society 2014
Subjects:	proximal-gradient method convex optimization exact penalty function method distributed algorithm
Online Access:	http://hdl.handle.net/20.500.11937/41558

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