Distributed constrained optimization and consensus in uncertain networks via proximal minimization

We provide a unifying framework for distributed convex optimization over time-varying networks, in the presence of constraints and uncertainty, features that are typically treated separately in the literature. We adopt a proximal minimization perspective and show that this set-up allows us to bypass...

詳細記述

書誌詳細
主要な著者: Margellos, K, Falsone, A, Garatti, S, Prandini, M
フォーマット: Journal article
出版事項: IEEE 2017