Joint Online Optimization of Model Training and Analog Aggregation for Wireless Edge Learning

Keyphrases

• Training Model 100%
• Model Optimization 100%
• Online Optimization 100%
• Analog Aggregation 100%
• Wireless Edge Learning 100%
• Online Model Updating 66%
• Global Model 41%
• Local Model 33%
• Edge Server 25%
• Mobile Devices 16%
• Aggregation Model 16%
• Performance Bounds 16%
• Transmit Power Constraint 16%
• Real Image 8%
• Communication Environment 8%
• Learning Algorithm 8%
• Performance Metrics 8%
• Low Computational Complexity 8%
• Power-aware 8%
• Result-oriented 8%
• Local Data 8%
• Image Classification 8%
• Classification Datasets 8%
• Wireless Networks 8%
• Performance Gain 8%
• Computational Performance 8%
• Federated Learning 8%
• Network Context 8%
• Gradient Aggregation 8%
• Communication Performance 8%
• Wireless Edge Networks 8%
• Adaptive Update 8%
• Convergence Time 8%
• Power Limit 8%
• Mutual Impact 8%
• Wireless Fading Channels 8%
• Best Alternative 8%
• Channel-aware 8%
• Double Regularization 8%
• Training Loss 8%
• Over-the-air Computation 8%

Computer Science

• Edge Server 100%
• Power Constraint 66%
• Mobile Device 66%
• Performance Bound 66%
• Computational Complexity 33%
• Regularization 33%
• Efficient Algorithm 33%
• Learning Algorithm 33%
• Communication Environment 33%
• Performance Metric 33%
• Image Classification 33%
• Wireless Network 33%
• Performance Gain 33%
• Fading Channel 33%
• Over-The-Air Computation 33%
• Federated machine learning 33%