Decentralized Federated Learning via SGD over Wireless D2D Networks

Keyphrases

• Analog Transmission 33%
• Blockage 33%
• Communication Range 33%
• Computing Resources 33%
• Convexity 33%
• Critical Enablers 33%
• D2D Networks 100%
• Data Computing 33%
• Decentralized Federated Learning 100%
• Decentralized Stochastic Gradient Descent 100%
• Device Sharing 33%
• Device-to-device 33%
• Digital Transmission 33%
• Distributed Datasets 33%
• Edge Devices 33%
• Emergent Paradigm 33%
• Empirical Risk Minimization 33%
• Federated Learning 100%
• Graph Coloring 33%
• Intelligent Acquisition 33%
• Joint Training 33%
• Limited Disclosure 33%
• Local Data 33%
• Local SGD 33%
• Machine Learning Models 33%
• Minimization Problem 33%
• Model Information 33%
• Mutual Interference 33%
• Network Edge 33%
• Over-the-air Computing 33%
• Path Loss 33%
• Physical Layer 33%
• Sparsity Basis 33%
• Training Set 33%
• Transmission Strategy 33%
• Wireless 100%
• Wireless Channel 33%
• Wireless Devices 33%
• Wireless Protocol 33%

Computer Science

• Average Consensus 25%
• Communication Range 25%
• Computing Resource 25%
• Device-To-Device 25%
• Federated Learning 100%
• Gradient Descent 75%
• Graph Coloring 25%
• Information Model 25%
• Machine Learning 25%
• Minimization Problem 25%
• Neighboring Device 25%
• Physical Layer 25%
• Risk Minimization 25%
• Sparsity 25%
• Wireless Channel 25%
• Wireless Device 25%