Linear Convergence Rate of a Class of Distributed Augmented Lagrangian Algorithms

DOI10.1109/TAC.2014.2363299zbMath1360.90199arXiv1307.2482MaRDI QIDQ2982765

João Xavier, José M. F. Moura, Dušan Jakovetić

Publication date: 16 May 2017

Published in: IEEE Transactions on Automatic Control (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1307.2482

Mathematics Subject Classification ID

Related Items (15)

Optimal Algorithms for Non-Smooth Distributed Optimization in Networks ⋮ Distributed Optimization Based on Gradient Tracking Revisited: Enhancing Convergence Rate via Surrogation ⋮ Cluster-based distributed augmented Lagrangian algorithm for a class of constrained convex optimization problems ⋮ A distributed methodology for approximate uniform global minimum sharing ⋮ Tracking-ADMM for distributed constraint-coupled optimization ⋮ Primal-dual \(\varepsilon\)-subgradient method for distributed optimization ⋮ Distributed stochastic gradient tracking methods with momentum acceleration for non-convex optimization ⋮ Distributed subgradient method for multi-agent optimization with quantized communication ⋮ Distributed optimization over directed graphs with row stochasticity and constraint regularity ⋮ Decentralized Consensus Algorithm with Delayed and Stochastic Gradients ⋮ Ontology Sparse Vector Learning Algorithm for Ontology Similarity Measuring and Ontology Mapping via ADAL Technology ⋮ Augmented Lagrange algorithms for distributed optimization over multi-agent networks via edge-based method ⋮ Distributed decision-coupled constrained optimization via proximal-tracking ⋮ A randomized incremental primal-dual method for decentralized consensus optimization ⋮ EXTRA: An Exact First-Order Algorithm for Decentralized Consensus Optimization

This page was built for publication: Linear Convergence Rate of a Class of Distributed Augmented Lagrangian Algorithms