Complexity analysis of interior-point methods for linear optimization based on some conditions on kernel function.
Keyvan AminiM. Reza PeyghamiPublished in: Appl. Math. Comput. (2006)
Keyphrases
- kernel function
- complexity analysis
- interior point methods
- quadratic programming
- semidefinite
- semidefinite programming
- support vector machine
- kernel matrix
- optimal kernel
- support vector
- linear programming
- convex optimization
- kernel methods
- input space
- feature space
- sufficient conditions
- linear systems
- theoretical analysis
- linear program
- kernel learning
- high dimensional
- lower bound
- first order logic
- reproducing kernel hilbert space
- support vector regression
- support vectors
- primal dual
- hyperplane
- ls svm
- computationally intensive
- linear combination
- feature set
- svm classifier
- convex relaxation
- feature selection
- machine learning
- solving problems
- multiple kernel learning
- maximum margin
- generalization ability
- data sets
- training data