Semi-proximal Augmented Lagrangian-Based Decomposition Methods for Primal Block-Angular Convex Composite Quadratic Conic Programming Problems.
Xin Yee LamDefeng SunKim-Chuan TohPublished in: INFORMS J. Optim. (2021)
Keyphrases
- decomposition methods
- augmented lagrangian
- duality gap
- convex optimization
- constrained optimization problems
- objective function
- primal dual
- decomposition method
- constrained optimization
- convex programming
- total variation
- lagrange multipliers
- convex functions
- conic programming
- databases
- motion estimation
- linear programming problems
- augmented lagrangian method
- support vector
- convex hull
- cost function
- computational complexity
- inequality constraints
- machine learning