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» Modelling Profiles with a Mixture of Gaussians
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BMCBI
2006
103views more  BMCBI 2006»
13 years 8 months ago
Probe-level linear model fitting and mixture modeling results in high accuracy detection of differential gene expression
Background: The identification of differentially expressed genes (DEGs) from Affymetrix GeneChips arrays is currently done by first computing expression levels from the low-level ...
Sébastien Lemieux
GIS
2010
ACM
13 years 6 months ago
Probabilistic modeling of traffic lanes from GPS traces
Instead of traditional ways of creating road maps, an attractive alternative is to create a map based on GPS traces of regular drivers. One important aspect of this approach is to...
Yihua Chen, John Krumm
CRV
2009
IEEE
132views Robotics» more  CRV 2009»
14 years 2 months ago
Non-Accidental Features for Gesture Spotting
In this paper we argue that gestures based on nonaccidental motion features can be reliably detected amongst unconstrained background motion. Specifically, we demonstrate that hu...
Adam Fourney, Richard Mann
NIPS
2001
13 years 9 months ago
Covariance Kernels from Bayesian Generative Models
We propose the framework of mutual information kernels for learning covariance kernels, as used in Support Vector machines and Gaussian process classifiers, from unlabeled task da...
Matthias Seeger
SAC
2011
ACM
13 years 2 months ago
Slice sampling mixture models
We propose a more efficient version of the slice sampler for Dirichlet process mixture models described by Walker (2007). This sampler allows the fitting of infinite mixture mod...
Maria Kalli, Jim E. Griffin, Stephen G. Walker