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» Simplifying mixture models through function approximation
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ICASSP
2009
IEEE
14 years 2 months ago
Bounded conditional mean imputation with Gaussian mixture models: A reconstruction approach to partly occluded features
In this work we show how conditional mean imputation can be bounded through the use of box-truncated Gaussian distributions. That is of interest when signals or features are partl...
Friedrich Faubel, John W. McDonough, Dietrich Klak...
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
ESANN
2007
13 years 9 months ago
Visualisation of tree-structured data through generative probabilistic modelling
We present a generative probabilistic model for the topographic mapping of tree structured data. The model is formulated as constrained mixture of hidden Markov tree models. A nat...
Nikolaos Gianniotis, Peter Tino
NAACL
2003
13 years 9 months ago
Implicit Trajectory Modeling through Gaussian Transition Models for Speech Recognition
It is well known that frame independence assumption is a fundamental limitation of current HMM based speech recognition systems. By treating each speech frame independently, HMMs ...
Hua Yu, Tanja Schultz
ISVC
2007
Springer
14 years 1 months ago
A New Set of Normalized Geometric Moments Based on Schlick's Approximation
Schlick’s approximation of the term xp is used primarily to reduce the complexity of specular lighting calculations in graphics applications. Since moment functions have a kernel...
Ramakrishnan Mukundan