Complexity analysis of infeasible interior-point method for semidefinite optimization based on a new trigonometric kernel function.
M. MoslemiBehrouz KheirfamPublished in: Optim. Lett. (2019)
Keyphrases
- semidefinite
- interior point methods
- positive semidefinite
- kernel function
- semidefinite programming
- kernel matrix
- convex optimization
- linear programming
- quadratic programming
- kernel methods
- linear program
- support vector
- convex relaxation
- primal dual
- feature space
- input space
- support vector machine
- computationally intensive
- support vectors
- solving problems
- higher dimensional
- sufficient conditions
- convex sets
- multiple kernel learning
- high dimensional
- hyperplane
- machine learning
- feature set
- pairwise
- feature extraction