Distributed Subgradient Method with Random Quantization and Flexible Weights: Convergence Analysis

Computer Science

• Quantization (Signal Processing) 100%
• Mathematical Convergence 100%
• Objective Function 66%
• Machine Learning 33%
• Optimization Problem 33%
• Distributed Optimization 33%
• Convergence Rate 33%
• Quantisation Error 33%
• Numerical Simulation 33%
• Privacy Concern 33%
• Transmission Link 33%
• Shared Information 33%

Mathematics

• Convergence Analysis 100%
• Subgradient 100%
• Objective Function 50%
• Step Size 50%
• Numerical Simulation 25%
• Upper Bound 25%
• Convergence Rate 25%
• Convex Case 25%
• Quantisation Error 25%

Keyphrases

• Random Vector Quantization 100%
• Weak Convexity 100%
• Weight Convergence 100%