The problem of nonlinear dimensionality reduction is considered. We focus on problems where prior information is available, namely, semi-supervised dimensionality reduction. It is...
Xin Yang, Haoying Fu, Hongyuan Zha, Jesse L. Barlo...
We propose a novel kernel regression algorithm which takes into account order preferences on unlabeled data. Such preferences have the form that point x1 has a larger target value...
We propose a novel ensemble learning algorithm called Triskel, which has two interesting features. First, Triskel learns an ensemble of classifiers, each biased to have high preci...
We present a search space analysis and its application in improving local search algorithms for the graph coloring problem. Using a classical distance measure between colorings, w...
Daniel Cosmin Porumbel, Jin-Kao Hao, Pascale Kuntz
The knowledge discovery process encounters the difficulties to analyze large amount of data. Indeed, some theoretical problems related to high dimensional spaces then appear and de...