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...
This work examines under what conditions compression methodologies can retain the outcome of clustering operations. We focus on the popular k-Means clustering algorithm and we dem...
Deepak S. Turaga, Michail Vlachos, Olivier Versche...
A general framework for performing robust, unsupervised tissue classification in magnetic resonance images is presented. Tissue classification is formulated as an estimation probl...
We propose a hierarchical, unsupervised clustering algorithm (TreeGCS) based upon the Growing Cell Structure (GCS) neural network of Fritzke. Our algorithm improves an inconsisten...
We consider the problem of retrieving multiple documents relevant to the single subtopics of a given web query, termed “full-subtopic retrieval”. To solve this problem we pres...
Andrea Bernardini, Claudio Carpineto, Massimiliano...