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Primal-Dual Method for Optimization Problems with Changing Constraints
Published 2 Jan 2022 in math.OC, cs.DC, and cs.MA | (2201.00334v1)
Abstract: We propose a modified primal-dual method for general convex optimization problems with changing constraints. We obtain properties of Lagrangian saddle points for these problems which enable us to establish convergence of the proposed method. We describe specializations of the proposed approach to multi-agent optimization problems under changing communication topology and to feasibility problems.
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