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...
| Main Authors: | , , , , |
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| Format: | Journal Article |
| Published: |
Australian Mathematical Society
2014
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| Subjects: | |
| Online Access: | http://hdl.handle.net/20.500.11937/41558 |