— This paper describes two performance measures for measuring an EMO (Evolutionary Multiobjective Optimization) algorithm’s ability to track a time-varying Paretofront in a dyn...
Genetic Programming offers freedom in the definition of the cost function that is unparalleled among supervised learning algorithms. However, this freedom goes largely unexploited...
The aim of this study is to propose an algorithm for simplifying color images. The assumption is made that a set of reference colors is available and that this set indicates which...
This paper presents a new way of thinking for IR metric optimization. It is argued that the optimal ranking problem should be factorized into two distinct yet interrelated stages:...
: A novel support vector machine method for classification is presented in this paper. A modified kernel function based on the similarity metric and Riemannian metric is applied ...