28 search results - page 3 / 6 » Post-nonlinear Independent Component Analysis by Variational... |
SSPR
2004
Springer
13 years 10 months ago
2004
Springer
We present a tutorial survey on some recent approaches to unsupervised machine learning in the context of statistical pattern recognition. In statistical PR, there are two classica...
ECCV
2000
Springer
14 years 6 months ago
2000
Springer
In recent years several techniques have been proposed for modelling the low-dimensional manifolds, or `subspaces', of natural images. Examples include principal component anal...
JMLR
2010
12 years 11 months ago
2010
We describe a novel inference algorithm for sparse Bayesian PCA with a zero-norm prior on the model parameters. Bayesian inference is very challenging in probabilistic models of t...
ECML
2007
Springer
13 years 11 months ago
2007
Springer
Abstract. Principal component analysis (PCA) is a well-known classical data analysis technique. There are a number of algorithms for solving the problem, some scaling better than o...
IJON
1998
13 years 4 months ago
1998
Bayesian Kullback Ying—Yang dependence reduction system and theory is presented. Via stochastic approximation, implementable algorithms and criteria are given for parameter lear...