Optimization of Graph Total Variation via Active-Set-based Combinatorial Reconditioning

Keyphrases

• Active Set 100%
• Set-based 100%
• Graph Total Variation 100%
• Local Linear Convergence 100%
• Proximal Algorithms 100%
• Computer Vision 50%
• Numerical Experiments 50%
• Machine Learning 50%
• Competitive Performance 50%
• Weighted Graph 50%
• Greedy Heuristic 50%
• Preconditioning Strategy 50%
• Primal-dual Hybrid Gradient Method 50%
• Local Convergence Analysis 50%
• Proximal Gradient Method 50%
• Variable Metric 50%
• Forest Decomposition 50%
• Structured Convex Optimization 50%
• Nested Decomposition 50%
• Problem Class 50%

Computer Science

• Convergence Rate 100%
• Total Variation 100%
• Convex Optimization 50%
• weighted graph 50%
• Greedy Heuristic 50%
• Preconditioner 50%
• Primal-Dual 50%
• Mathematical Convergence 50%
• Machine Learning 50%
• Learning System 50%
• Computer Vision 50%

Mathematics

• Total Variation 100%
• Linear Convergence 100%
• Convergence Rate 100%
• Edge 50%
• Local Convergence Analysis 50%
• Numerical Experiment 50%
• weighted graph 50%