DQM: Decentralized Quadratically Approximated Alternating Direction Method of Multipliers

DOI10.1109/TSP.2016.2548989zbMath1414.90270arXiv1508.02073MaRDI QIDQ4620969

Aryan Mokhtari, Wei Shi, Qing Ling, Alejandro Ribeiro

Publication date: 8 February 2019

Published in: IEEE Transactions on Signal Processing (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1508.02073

Mathematics Subject Classification ID

Convex programming (90C25) Signal theory (characterization, reconstruction, filtering, etc.) (94A12) Methods of successive quadratic programming type (90C55)

Related Items

Optimal Algorithms for Non-Smooth Distributed Optimization in Networks ⋮ Distributed Optimization Based on Gradient Tracking Revisited: Enhancing Convergence Rate via Surrogation ⋮ Distributed support vector machine in master-slave mode ⋮ Decentralized ADMM with compressed and event-triggered communication ⋮ Distributed Nash equilibrium learning: A second‐order proximal algorithm ⋮ Distributed finite-time optimisation of multi-agent systems with unknown high-frequency gain signs under switching digraphs ⋮ Distributed convex optimization as a tool for solving \(f\)-consensus problems ⋮ Graph Topology Invariant Gradient and Sampling Complexity for Decentralized and Stochastic Optimization ⋮ Distributed nonconvex constrained optimization over time-varying digraphs ⋮ Achieving Geometric Convergence for Distributed Optimization Over Time-Varying Graphs ⋮ Exact spectral-like gradient method for distributed optimization ⋮ Communication-efficient algorithms for decentralized and stochastic optimization ⋮ Unnamed Item ⋮ Newton-like Method with Diagonal Correction for Distributed Optimization