Non-linear dimensionality reduction of noisy data is a challenging problem encountered in a variety of data analysis applications. Recent results in the literature show that spect...
Scientific workflow tools allow users to specify complex computational experiments and provide a good framework for robust science and engineering. Workflows consist of pipelines ...
David Abramson, Blair Bethwaite, Colin Enticott, S...
In this paper, we present a novel on-line probabilistic generative model that simultaneously deals with both the clustering and the tracking of an unknown number of moving objects...
— Network clustering enables us to view a complex network at the macro level, by grouping its nodes into units whose characteristics and interrelationships are easier to analyze ...
In this paper we propose a new clustering algorithm which combines the FCM clustering algorithm with the supervised learning normal mixture model; we call the algorithm as the FCM...