Exploiting diversity via importance-aware user scheduling for fast edge learning

Keyphrases

• Edge Learning 100%
• User Scheduling 100%
• Data Importance 50%
• Signal-to-noise Ratio 25%
• Scheduling Decisions 25%
• Noisy Data 25%
• Scheduling Scheme 25%
• Network Reliability 25%
• Scheduling Method 25%
• Scheduling Algorithm 25%
• Support Vector Machine 25%
• Promising Technology 25%
• Training Model 25%
• Multiuser Diversity 25%
• Uncertain Data 25%
• Network Edge 25%
• Intelligent Mobile Applications 25%
• Edge Server 25%
• Edge Devices 25%
• Fast Model 25%
• Learning Perspective 25%
• Distance to the Decision Boundary 25%
• Multiuser Channels 25%
• Importance Indicator 25%
• Importance Metric 25%
• User Scheduling Algorithm 25%
• Intelligence Acquisition 25%
• Model Convergence 25%
• Radio Resources 25%

Computer Science

• Scheduling Algorithm 100%
• Training Model 50%
• Edge Server 50%
• Scheduling Scheme 50%
• Scheduling Method 50%
• Noise-to-Signal Ratio 50%
• multiuser diversity 50%
• Mobile Application 50%
• Decision Boundary 50%
• Support Vector Machine 50%