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Organizing Web search results into clusters facilitates users' quick browsing through search results. Traditional clustering techniques are inadequate since they don't generate clusters with highly readable names. In this paper, we reformalize the clustering problem as a salient phrase ranking problem. Given a query and the ranked list of documents(More)
Automated cell segmentation and tracking are critical for quantitative analysis of cell cycle behavior using time-lapse fluorescence microscopy. However, the complex, dynamic cell cycle behavior poses new challenges to the existing image segmentation and tracking methods. This paper presents a fully automated tracking method for quantitative cell cycle(More)
Gaussian mixture modelling is a powerful tool for data analysis. However, the selection of number of Gaussians in the mixture, i.e., the mixture model or scale selection, remains a difficult problem. In this paper , we propose a new kind of dynamic merge-or-split learning (DMOSL) algorithm on Gaussian mixture such that the number of Gaussians can be(More)
One important feature of Bayesian Ying–Yang (BYY) harmony learning is that model selection can be made automatically during parametric learning. In this paper, BYY harmony learning with a bi-directional architecture is studied for Gaussian mixture modelling via a gradient learning rule. It has been demonstrated by simulation experiments that the number of(More)
It is well known that the convergence rate of the expectation-maximization (EM) algorithm can be faster than those of convention rst-order iterative algorithms when the overlap in the given mixture is small. But this argument has not been mathematically proved yet. This article studies this problem asymptotically in the setting of gaussian mixtures under(More)