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» Relevant subtask learning by constrained mixture models
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BMCBI
2007
133views more  BMCBI 2007»
13 years 7 months ago
Semi-supervised learning for the identification of syn-expressed genes from fused microarray and in situ image data
Background: Gene expression measurements during the development of the fly Drosophila melanogaster are routinely used to find functional modules of temporally co-expressed genes. ...
Ivan G. Costa, Roland Krause, Lennart Opitz, Alexa...
TASLP
2008
124views more  TASLP 2008»
13 years 7 months ago
Semantic Annotation and Retrieval of Music and Sound Effects
We present a computer audition system that can both annotate novel audio tracks with semantically meaningful words and retrieve relevant tracks from a database of unlabeled audio c...
Douglas Turnbull, Luke Barrington, D. Torres, Gert...
BMCBI
2008
134views more  BMCBI 2008»
13 years 7 months ago
Stability analysis of mixtures of mutagenetic trees
Background: Mixture models of mutagenetic trees are evolutionary models that capture several pathways of ordered accumulation of genetic events observed in different subsets of pa...
Jasmina Bogojeska, Thomas Lengauer, Jörg Rahn...
NIPS
2004
13 years 9 months ago
Sampling Methods for Unsupervised Learning
We present an algorithm to overcome the local maxima problem in estimating the parameters of mixture models. It combines existing approaches from both EM and a robust fitting algo...
Robert Fergus, Andrew Zisserman, Pietro Perona
BMCBI
2010
171views more  BMCBI 2010»
13 years 7 months ago
PyMix - The Python mixture package - a tool for clustering of heterogeneous biological data
Background: Cluster analysis is an important technique for the exploratory analysis of biological data. Such data is often high-dimensional, inherently noisy and contains outliers...
Benjamin Georgi, Ivan Gesteira Costa, Alexander Sc...