An Exact Penalty Method for Semidefinite-Box-Constrained Low-Rank Matrix Optimization Problems

Keyphrases

• Optimization Problem 100%
• Box-constrained 100%
• Penalty Problem 100%
• Semidefinite 100%
• Exact Penalty Function 100%
• Non-monotone 100%
• Proximal Gradient Method 100%
• Low-rank Matrix Approximation 100%
• Original Problem 66%
• Rank Constraint 66%
• Adaptive Penalty Function 66%
• Newton's Method 33%
• Stationary Point 33%
• First-order 33%
• Penalty Function 33%
• Quadratic Convergence 33%
• Continuously Differentiable Function 33%
• Numerical Experiments 33%
• Localization Problem 33%
• Box Constraints 33%
• Non-Lipschitz 33%
• Sensor Node Localization 33%
• Matrix Problem 33%
• Matrix Optimization 33%
• Low-rank Correlation Matrix 33%

Mathematics

• Matrix 100%
• Penalty Method 100%
• Stationary Point 33%
• Objective Function 33%
• Correlation Matrix 33%
• Spearman's Coefficient 33%
• Numerical Experiment 33%
• Newton's Method 33%
• Subproblem 33%