A generic primal-dual interior-point method for semidefinite optimization based on a new class of kernel functions.
Mohamed El GhamiCornelis RoosTrond SteihaugPublished in: Optim. Methods Softw. (2010)
Keyphrases
- semidefinite
- interior point methods
- primal dual
- kernel function
- semidefinite programming
- kernel matrix
- convex optimization
- linear programming
- interior point
- linear program
- support vector
- linear programming problems
- quadratic programming
- reproducing kernel hilbert space
- support vector machine
- approximation algorithms
- kernel methods
- convergence rate
- variational inequalities
- analytic center
- solving problems
- feature space
- hyperplane
- input space
- support vectors
- computationally intensive
- finite number
- total variation
- svm classifier
- sufficient conditions
- dynamic programming
- high dimensional