In situations where class labels are known for a part of the objects, a cluster analysis respecting this information, i.e. semi-supervised clustering, can give insight into the cl...
In this paper, an easily implemented semi-supervised graph learning method is presented for dimensionality reduction and clustering, using the most of prior knowledge from limited...
An algorithm for combining results of different clusterings is presented in this paper, the objective of which is to find groups of patterns which are common to all clusterings. T...
In this paper, we consider the clustering of resources on large scale platforms. More precisely, we target parallel applications consisting of independant tasks, where each task is...
Olivier Beaumont, Nicolas Bonichon, Philippe Ducho...
Density estimation with Gaussian Mixture Models is a popular generative technique used also for clustering. We develop a framework to incorporate side information in the form of e...