We present a novel algorithm for agglomerative hierarchical clustering based on evaluating marginal likelihoods of a probabilistic model. This algorithm has several advantages ove...
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....
In this paper we describe a method of learning hierarchical representations for describing and recognizing gestures expressed as one and two arm movements using competitive learni...
—This paper addresses the simulation of the dynamics of complex systems by using hierarchical graph and multi-agent system. A complex system is composed of numerous interacting p...
To deal with the issue of data unbalanced condition among a task of multilingual speech recognition and a phenomenon of pronunciation variations across languages, we propose an ap...