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157
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PRL
2007
154views more  PRL 2007»
15 years 2 months ago
Regularized mixture discriminant analysis
Abstract – In this paper we seek a Gaussian mixture model (GMM) of the classconditional densities for plug-in Bayes classification. We propose a method for setting the number of ...
Zohar Halbe, Mayer Aladjem
110
Voted
ISMB
2001
15 years 3 months ago
Using mixtures of common ancestors for estimating the probabilities of discrete events in biological sequences
Accurately estimating probabilities from observations is important for probabilistic-based approaches to problems in computational biology. In this paper we present a biologically...
Eleazar Eskin, William Noble Grundy, Yoram Singer
168
Voted
ICTAI
2010
IEEE
14 years 12 months ago
Unsupervised Greedy Learning of Finite Mixture Models
This work deals with a new technique for the estimation of the parameters and number of components in a finite mixture model. The learning procedure is performed by means of a expe...
Nicola Greggio, Alexandre Bernardino, Cecilia Lasc...
129
Voted
DAGM
2010
Springer
15 years 3 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
DSP
2007
15 years 2 months ago
Blind separation of nonlinear mixtures by variational Bayesian learning
Blind separation of sources from nonlinear mixtures is a challenging and often ill-posed problem. We present three methods for solving this problem: an improved nonlinear factor a...
Antti Honkela, Harri Valpola, Alexander Ilin, Juha...