University of Illinois at Urbana-ChampaignUrbana, ILhbdeng@illinois.edu
University of Illinois at Urbana-ChampaignUrbana, ILhanj@illinois.edu
Probabilistic model-based clustering techniques have been widely used and have shown promising results in many applications, ranging from image segmentation [71, 15], handwriting recognition , document clustering [36, 81], topic modeling [35, 14] to information retrieval . Model-based clustering approaches attempt to optimize the fit between the observed data and some mathematical model using a probabilistic approach. Such methods are often based on the assumption that the data are generated by a mixture of underlying ...