Distributed Saddle-Point Subgradient Algorithms With Laplacian Averaging
From MaRDI portal
Publication:5352624
DOI10.1109/TAC.2016.2616646zbMath1369.90193arXiv1510.05169OpenAlexW2963128910MaRDI QIDQ5352624
David Mateos-Núñez, Jorge Cortés
Publication date: 8 September 2017
Published in: IEEE Transactions on Automatic Control (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1510.05169
Related Items (11)
A unitary distributed subgradient method for multi-agent optimization with different coupling sources ⋮ Distributed constraint-coupled optimization via primal decomposition over random time-varying graphs ⋮ Tracking-ADMM for distributed constraint-coupled optimization ⋮ Two-timescale recurrent neural networks for distributed minimax optimization ⋮ Composite optimization with coupling constraints via dual proximal gradient method with applications to asynchronous networks ⋮ Decentralized Gradient Descent Maximization Method for Composite Nonconvex Strongly-Concave Minimax Problems ⋮ A Unified Framework for Continuous-Time Unconstrained Distributed Optimization ⋮ Distributed algorithms for computing a fixed point of multi-agent nonexpansive operators ⋮ Cooperative convex optimization with subgradient delays using push-sum distributed dual averaging ⋮ A Distributed ADMM-like Method for Resource Sharing over Time-Varying Networks ⋮ Solving a class of nonsmooth resource allocation problems with directed graphs through distributed Lipschitz continuous multi-proximal algorithms
This page was built for publication: Distributed Saddle-Point Subgradient Algorithms With Laplacian Averaging