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» Learning Mixtures of Gaussians
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NIPS
2003
15 years 7 months ago
Gene Expression Clustering with Functional Mixture Models
We propose a functional mixture model for simultaneous clustering and alignment of sets of curves measured on a discrete time grid. The model is specifically tailored to gene exp...
Darya Chudova, Christopher E. Hart, Eric Mjolsness...
TSP
2011
125views more  TSP 2011»
15 years 1 months ago
Weight Adjusted Tensor Method for Blind Separation of Underdetermined Mixtures of Nonstationary Sources
—In this paper, a novel algorithm to blindly separate an instantaneous linear underdetermined mixture of nonstationary sources is proposed. It means that the number of sources ex...
Petr Tichavský, Zbynek Koldovský
ICASSP
2011
IEEE
14 years 10 months ago
Integrating binaural cues and blind source separation method for separating reverberant speech mixtures
This paper presents a new method for reverberant speech separation, based on the combination of binaural cues and blind source separation (BSS) for the automatic classification o...
Atiyeh Alinaghi, Wenwu Wang, Philip J. B. Jackson
INFOCOM
2009
IEEE
16 years 1 months ago
Robust Event Boundary Detection in Sensor Networks - A Mixture Model Based Approach
—Detecting event frontline or boundary sensors in a complex sensor network environment is one of the critical problems for sensor network applications. In this paper, we propose ...
Min Ding, Xiuzhen Cheng
ICIP
2009
IEEE
15 years 4 months ago
Random swap EM algorithm for finite mixture models in image segmentation
The Expectation-Maximization (EM) algorithm is a popular tool in statistical estimation problems involving incomplete data or in problems which can be posed in a similar form, suc...
Qinpei Zhao, Ville Hautamäki, Ismo Kärkk...