An improved convergence analysis of cyclic block coordinate descent-type methods for strongly convex minimization

Keyphrases

• Convergence Analysis 100%
• Block Coordinate Descent 100%
• Improved Convergence 100%
• Cyclic Blocks 100%
• Strongly Convex Minimization 100%
• Iteration Complexity 60%
• Complexity Bounds 40%
• P Factor 40%
• Convex Minimization Problem 40%
• Tight 20%
• Eigenvalues 20%
• Hessian Matrix 20%
• Typical Application 20%
• Quadratic Minimization Problem 20%
• Objective Value 20%
• Gradient Method 20%
• Elastic Net Regression 20%
• Penalized Logistic Regression 20%
• Additive Regression 20%
• GD Method 20%
• Popular 20%
• Computational Performance 20%
• Statistical Machine Learning Methods 20%
• Number of Blocks 20%

Mathematics

• Type Method 100%
• Convergence Analysis 100%
• Convex Minimization 100%
• Convex Minimization Problem 40%
• Elastic Net 20%
• Ridge Regression 20%
• Penalized Logistic Regression 20%
• Minimization Problem 20%
• Eigenvalue 20%
• Hessian Matrix 20%