On approximate solutions and saddle point theorems for robust convex optimization.
Xiang-Kai SunKok Lay TeoJing ZengXiao-Le GuoPublished in: Optim. Lett. (2020)
Keyphrases
- convex optimization
- approximate solutions
- primal dual
- saddle point
- interior point
- interior point methods
- structured prediction
- low rank
- convex relaxation
- total variation
- variational inequalities
- np hard
- exact solution
- semidefinite programming
- convergence rate
- linear programming
- convex sets
- natural images
- computer vision
- special case
- optimal solution
- objective function
- linear programming problems
- similarity measure
- image segmentation