In the last 25 years approximation algorithms for discrete optimization problems have been in the center of research in the fields of mathematical programming and computer science...
This paper addresses cost-sensitive classification in the setting where there are costs for measuring each attribute as well as costs for misclassification errors. We show how to ...
Heuristics have long been recognised as a way to tackle problems which are intractable because of their size or complexity. They have been used in software engineering for purpose...
Neville Churcher, Sarah Frater, Cong Phuoc Huynh, ...
We address distributed real-time applications represented by systems of non-preemptive dependent periodic tasks. This system is described by an acyclic directed graph. Because the...
Rule induction from examples is a machine learning technique that finds rules of the form condition → class, where condition and class are logic expressions of the form variable...