Complexity analysis of primal-dual interior-point methods for linear optimization based on a new efficient Bi-parameterized kernel function with a trigonometric barrier term.
Mousaab BouafiaAdnan YassinePublished in: RAIRO Oper. Res. (2022)
Keyphrases
- interior point methods
- complexity analysis
- primal dual
- kernel function
- quadratic programming
- semidefinite
- convex programming
- semidefinite programming
- convex optimization
- linear programming
- interior point
- support vector machine
- linear program
- kernel matrix
- linear programming problems
- interior point algorithm
- linear systems
- feature space
- computationally intensive
- input space
- support vector
- kernel methods
- theoretical analysis
- computational complexity
- solving problems
- lower bound
- kernel learning
- convergence rate
- first order logic
- optimal kernel
- hyperplane
- approximation algorithms
- upper bound
- ls svm
- convex relaxation
- feature set
- special case
- high dimensional