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» An extension of the ICA model using latent variables
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ICML
2005
IEEE
15 years 10 months ago
Recognition and reproduction of gestures using a probabilistic framework combining PCA, ICA and HMM
This paper explores the issue of recognizing, generalizing and reproducing arbitrary gestures. We aim at extracting a representation that encapsulates only the key aspects of the ...
Sylvain Calinon, Aude Billard
NECO
1998
116views more  NECO 1998»
14 years 9 months ago
GTM: The Generative Topographic Mapping
Latent variable models represent the probability density of data in a space of several dimensions in terms of a smaller number of latent, or hidden, variables. A familiar example ...
Christopher M. Bishop, Markus Svensén, Chri...
ICA
2010
Springer
14 years 11 months ago
Binary Sparse Coding
We study a sparse coding learning algorithm that allows for a simultaneous learning of the data sparseness and the basis functions. The algorithm is derived based on a generative m...
Marc Henniges, Gervasio Puertas, Jörg Bornsch...
DAGM
2010
Springer
14 years 11 months ago
Gaussian Mixture Modeling with Gaussian Process Latent Variable Models
Density modeling is notoriously difficult for high dimensional data. One approach to the problem is to search for a lower dimensional manifold which captures the main characteristi...
Hannes Nickisch, Carl Edward Rasmussen
SDM
2008
SIAM
206views Data Mining» more  SDM 2008»
14 years 11 months ago
Latent Variable Mining with Its Applications to Anomalous Behavior Detection
In this paper, we propose a new approach to anomaly detection by looking at the latent variable space to make the first step toward latent anomaly detection. Most conventional app...
Shunsuke Hirose, Kenji Yamanishi