Previous works on automatic query clustering most generate a flat, un-nested partition of query terms. In this work, we are pursuing to organize query terms into a hierarchical s...
The problem of assessing the reliability of clusters patients identified by clustering algorithms is crucial to estimate the significance of subclasses of diseases detectable at b...
We introduce a new method for data clustering based on a particular Gaussian mixture model (GMM). Each cluster of data, modeled as a GMM into an input space, is interpreted as a hy...
Power consumption is an important issue for cluster supercomputers as it directly affects running cost and cooling requirements. This paper investigates the memory energy efficienc...
Mean-Shift (MS) is a powerful non-parametric clustering method. Although good accuracy can be achieved, its computational cost is particularly expensive even on moderate data sets...