On semidefinite programming relaxations for a class of robust SOS-convex polynomial optimization problems.
Xiang-Kai SunJiayi HuangKok Lay TeoPublished in: J. Glob. Optim. (2024)
Keyphrases
- semidefinite programming
- semidefinite
- quadratically constrained quadratic
- positive semidefinite
- optimization problems
- linear matrix inequality
- linear programming
- nonlinear programming
- interior point methods
- convex optimization
- semi infinite
- quadratic function
- evolutionary algorithm
- kernel matrix
- primal dual
- objective function
- convex relaxation
- maximum margin
- finite dimensional
- optimization methods
- semi definite programming
- globally optimal
- kernel learning
- linear program
- class labels
- kernel function
- linear combination
- sufficient conditions
- np hard
- lower bound