We consider a semi-supervised setting for domain adaptation where only unlabeled data is available for the target domain. One way to tackle this problem is to train a generative m...
We present an EM-based clustering method that can be used for constructing or augmenting ontologies such as MeSH. Our algorithm simultaneously clusters verbs and nouns using both ...
Vasileios Kandylas, Lyle H. Ungar, Ted Sandler, Sh...
Many systems in sciences, engineering and nature can be modeled as networks. Examples are internet, metabolic networks and social networks. Network clustering algorithms aimed to ...
Nurcan Yuruk, Mutlu Mete, Xiaowei Xu, Thomas A. J....
We propose in this paper an exploratory analysis algorithm for functional data. The method partitions a set of functions into K clusters and represents each cluster by a simple pr...
A method for structural clustering is proposed involving data on subset-to-entity linkages that can be calculated with structural data such as graphs or sequences or images. The m...