Clustering is a central unsupervised learning task with a wide variety of applications. Not surprisingly, there exist many clustering algorithms. However, unlike classification ta...
Spectral clustering refers to a flexible class of clustering procedures that can produce high-quality clusterings on small data sets but which has limited applicability to large-...
Christopher Leckie, James C. Bezdek, Kotagiri Rama...
Document clustering is useful in many information retrieval tasks: document browsing, organization and viewing of retrieval results, generation of Yahoo-like hierarchies of docume...
Since a large number of clustering algorithms exist, aggregating different clustered partitions into a single consolidated one to obtain better results has become an important pro...
In this paper, we presentan approach to clustering images for efficient retrieval using relative entropy. We start with the assumption that visual features are represented by prob...