Likelihood-based marginal regression modelling for repeated, or otherwise clustered, categorical responses is computationally demanding. This is because the number of measures nee...
In this paper a new approach for face clustering is developed. Mutual information and joint entropy are exploited in order to create a metric for the clustering process. The way t...
Nicholas Vretos, Vassilios Solachidis, Ioannis Pit...
Clustering ensembles has been recently recognized as an emerging approach to provide more robust solutions to the data clustering problem. Current methods of clustering ensembles ...
- Clustering plays an indispensable role for data analysis. Many clustering algorithms have been developed. However, most of them suffer either poor performance of unsupervised lea...
The identification of clusters, well-connected components in a graph, is useful in many applications from biological function prediction to social community detection. However, ...