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» Simplifying Mixture Models Using the Unscented Transform
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ICML
2005
IEEE
14 years 8 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»
13 years 8 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
JAIR
2010
108views more  JAIR 2010»
13 years 6 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
14 years 8 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
14 years 2 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...