In our previous work, we have developed sparse least squares support vector regressors (sparse LS SVRs) trained in the primal form in the reduced empirical feature space. In this p...
Abstract. Taking inspiration from approximate ranking, this paper investigates the use of rank-based Support Vector Machine as surrogate model within CMA-ES, enforcing the invarian...
The Shortest Common Supersequence problem is a hard combinatorial optimization problem with numerous practical applications. Several evolutionary approaches are proposed for this p...
In the previous years some authors have been elaborating on the measurementtheoretic foundations of fuzzy set theory. A well-known problem in this approach is the difficult applic...