Recycled ADMM: Improving the Privacy and Accuracy of Distributed Algorithms

Alternating direction method of multiplier (ADMM) is a powerful method to solve decentralized convex optimization problems. In distributed settings, each node performs computation with its local data and the local results are exchanged among neighboring nodes in an iterative fashion. During this ite...

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Veröffentlicht in:	IEEE transactions on information forensics and security 2020, Vol.15, p.1723-1734
Hauptverfasser:	Zhang, Xueru, Khalili, Mohammad Mahdi, Liu, Mingyan
Format:	Artikel
Sprache:	eng
Schlagworte:	Accuracy ADMM Algorithms Computational geometry Convergence Convexity Differential privacy Distributed databases distributed learning Iterative methods Mathematical analysis Optimization Perturbation methods Privacy Tradeoffs
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