Recent study has shown that canonical algorithms such as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) can be obtained from graph based dimensionality ...
The advances in kernel-based learning necessitate the study on solving a large-scale non-sparse positive definite linear system. To provide a deterministic approach, recent resear...
In this paper the Minimum Linear Arrangement (MinLA) problem is studied within the framework of memetic algorithms (MA). A new dedicated recombination operator called Trajectory Cr...
Eduardo Rodriguez-Tello, Jin-Kao Hao, Jose Torres-...
We consider the problem of learning in multilayer feed-forward networks of linear threshold units. We show that the Vapnik-Chervonenkis dimension of the class of functions that ca...
In this paper we address a general Goal Programming problem with linear objectives, convex constraints, and an arbitrary componentwise nondecreasing norm to aggregate deviations w...