182 search results - page 10 / 37 » Component-wise parameter smoothing for learning mixture mode... |
KDD
2002
ACM
15 years 10 months ago
2002
ACM
We propose mixtures of hidden Markov models for modelling clickstreams of web surfers. Hence, the page categorization is learned from the data without the need for a (possibly cumb...
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DAGM
2010
Springer
14 years 10 months ago
2010
Springer
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...
110
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CVPR
2005
IEEE
15 years 11 months ago
2005
IEEE
In [1], three popular subspace face recognition methods, PCA, Bayes, and LDA were analyzed under the same framework and an unified subspace analysis was proposed. However, since t...
BMEI
2009
IEEE
14 years 10 months ago
2009
IEEE
The Gaussian mixture model is a powerful statistical tool in data modeling and analysis. Generally, the EM algorithm is utilized to learn the parameters of the Gaussian mixture. Ho...
CSDA
2007
14 years 9 months ago
2007
Variational methods for model comparison have become popular in the neural computing/machine learning literature. In this paper we explore their application to the Bayesian analys...