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2008
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Robust estimation of gaussian mixtures from noisy input data

13 years 1 months ago
Robust estimation of gaussian mixtures from noisy input data
We propose a variational bayes approach to the problem of robust estimation of gaussian mixtures from noisy input data. The proposed algorithm explicitly takes into account the uncertainty associated with each data point, makes no assumptions about the structure of the covariance matrices and is able to automatically determine the number of the gaussian mixture components. Through the use of both synthetic and real world data examples, we show that by incorporating uncertainty information into the clustering algorithm, we get better results at recovering the true distribution of the training data compared to other variational bayesian clustering algorithms.
Shaobo Hou, Aphrodite Galata
Added 12 Oct 2009
Updated 28 Oct 2009
Type Conference
Year 2008
Where CVPR
Authors Shaobo Hou, Aphrodite Galata
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