Distributed Newton methods for strictly convex consensus optimization problems in multi-agent networks
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Publication:2333555
DOI10.3390/sym9080163zbMath1423.90190OpenAlexW2747021333MaRDI QIDQ2333555
Publication date: 13 November 2019
Published in: Symmetry (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.3390/sym9080163
spanning treematrix decompositiondistributed optimizationconsensus optimizationdistributed Newton methods
Uses Software
Cites Work
- Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
- Distributed stochastic subgradient projection algorithms for convex optimization
- A new class of distributed optimization algorithms: application to regression of distributed data
- Convergence of Iterates of an Inexact Matrix Splitting Algorithm for the Symmetric Monotone Linear Complementarity Problem
- An Adaptive Projected Subgradient Approach to Learning in Diffusion Networks
- Distributed Robust Multicell Coordinated Beamforming With Imperfect CSI: An ADMM Approach
- D-ADMM: A Communication-Efficient Distributed Algorithm for Separable Optimization
- On the Linear Convergence of the ADMM in Decentralized Consensus Optimization
- Network Newton Distributed Optimization Methods
- Distributed Subgradient Methods for Multi-Agent Optimization
- Distributed Subgradient Methods for Convex Optimization Over Random Networks
- A Distributed Newton Method for Network Utility Maximization–I: Algorithm
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