We present a new, statistical approach to rule learning. Doing so, we address two of the problems inherent in traditional rule learning: The computational hardness of finding rule...
RELIEF is considered one of the most successful algorithms for assessing the quality of features. In this paper, we propose a set of new feature weighting algorithms that perform s...
This paper develops algorithms to train linear support vector machines (SVMs) when training data are distributed across different nodes and their communication to a centralized no...
Pedro A. Forero, Alfonso Cano, Georgios B. Giannak...
We present a method that computes a global potentially visible set for the complete region outside the convex hull of an object. The technique is used to remove invisible parts (t...
Interval coefficients have been introduced in OR and CP to specify uncertain data in order to provide reliable solutions to convex models. The output is generally a solution set, ...