首页|Investigators at Shenzhen University Describe Findings in Intelligent Systems (Fedisp: an Incremental Subgradient-proximal-based Ringtype Architecture for Decentralized Federated Learning)
Investigators at Shenzhen University Describe Findings in Intelligent Systems (Fedisp: an Incremental Subgradient-proximal-based Ringtype Architecture for Decentralized Federated Learning)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Current study results on Machine Learning - Intelligent Systems have been published.According to news reporting from Shenzhen, People’s Republic of China, by NewsRx journalists, researchstated, “Federated learning (FL) represents a promising distributed machine learning paradigm for resolvingdata isolation due to data privacy concerns. Nevertheless, most vanilla FL algorithms, which depend on aserver, encounter the problem of reliability and a high communication burden in real cases.”
ShenzhenPeople’s Republic of ChinaAsiaIntelligent SystemsMachine LearningShenzhen University
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