In distributed data mining models, adopting a flat node distribution model can affect scalability. To address the problem of modularity, flexibility and scalability, we propose...
While crowds of various subjects may offer applicationspecific cues to detect individuals, we demonstrate that for the general case, motion itself contains more information than p...
Recent works in object recognition often use visual words, i.e. vector quantized local descriptors extracted from the images. In this paper we present a novel method to build such ...
Clustering is an important technique for understanding and analysis of large multi-dimensional datasets in many scientific applications. Most of clustering research to date has be...
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...