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» Hierarchical Gaussian process latent variable models
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139
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IJNS
2010
106views more  IJNS 2010»
15 years 2 months ago
Cascade Process Modeling with Mechanism-Based Hierarchical Neural Networks
Abstract: Cascade process, such as wastewater treatment plant, includes many nonlinear subsystems and many variables. When the number of sub-systems is big, the input-output relati...
Qiumei Cong, Wen Yu, Tianyou Chai
ICIP
2007
IEEE
16 years 5 months ago
Image Denoising with Nonparametric Hidden Markov Trees
We develop a hierarchical, nonparametric statistical model for wavelet representations of natural images. Extending previous work on Gaussian scale mixtures, wavelet coefficients ...
Jyri J. Kivinen, Erik B. Sudderth, Michael I. Jord...
PKDD
2010
Springer
154views Data Mining» more  PKDD 2010»
15 years 2 months ago
Topic Models Conditioned on Relations
Latent Dirichlet allocation is a fully generative statistical language model that has been proven to be successful in capturing both the content and the topics of a corpus of docum...
Mirwaes Wahabzada, Zhao Xu, Kristian Kersting
ICIP
2005
IEEE
16 years 5 months ago
SAR images as mixtures of Gaussian mixtures
We consider the problem of image segmentation by clustering local histograms with parametric mixture-of-mixture models. These models represent each cluster by a single mixture mod...
Peter Orbanz, Joachim M. Buhmann
151
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ICASSP
2008
IEEE
15 years 10 months ago
Fast speaker adaptation using non-negative matrix factorization
This paper describes a new method for fast speaker adaptation in large vocabulary recognition systems. As in most HMM-based recognizers, the observation densities are modeled as a...
Jacques Duchateau, Tobias Leroy, Kris Demuynck, Hu...