Proximal minimization based distributed convex optimization
We provide a novel iterative algorithm for distributed convex optimization over time-varying multi-agent networks, in the presence of heterogeneous agent constraints. We adopt a proximal minimization perspective and show that this set-up allows us to bypass the difficulties of existing algorithms wh...
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Institute of Electrical and Electronics Engineers
2016
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