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» Simplifying Mixture Models Using the Unscented Transform
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95
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ICML
2005
IEEE
15 years 10 months ago
Supervised dimensionality reduction using mixture models
Given a classification problem, our goal is to find a low-dimensional linear transformation of the feature vectors which retains information needed to predict the class labels. We...
Sajama, Alon Orlitsky
BMCBI
2010
140views more  BMCBI 2010»
14 years 9 months ago
Quantification and deconvolution of asymmetric LC-MS peaks using the bi-Gaussian mixture model and statistical model selection
Background: Liquid chromatography-mass spectrometry (LC-MS) is one of the major techniques for the quantification of metabolites in complex biological samples. Peak modeling is on...
Tianwei Yu, Hesen Peng
77
Voted
JAIR
2010
108views more  JAIR 2010»
14 years 8 months ago
Kalman Temporal Differences
This paper deals with value (and Q-) function approximation in deterministic Markovian decision processes (MDPs). A general statistical framework based on the Kalman filtering pa...
Matthieu Geist, Olivier Pietquin
IPMI
2007
Springer
15 years 10 months ago
Multi-fiber Reconstruction from Diffusion MRI Using Mixture of Wisharts and Sparse Deconvolution
Abstract. In this paper, we present a novel continuous mixture of diffusion tensors model for the diffusion-weighted MR signal attenuation. The relationship between the mixing dist...
Bing Jian, Baba C. Vemuri
ICASSP
2008
IEEE
15 years 4 months ago
Gradient steepness metrics using extended Baum-Welch transformations for universal pattern recognition tasks
In many pattern recognition tasks, given some input data and a family of models, the “best” model is defined as the one which maximizes the likelihood of the data given the m...
Tara N. Sainath, Dimitri Kanevsky, Bhuvana Ramabha...