292 search results - page 1 / 59 » Grammatical inference as a principal component analysis prob... |
ICML
2009
IEEE
13 years 11 months ago
2009
IEEE
One of the main problems in probabilistic grammatical inference consists in inferring a stochastic language, i.e. a probability distribution, in some class of probabilistic models...
AAAI
2004
13 years 6 months ago
2004
Based on the probabilistic reformulation of principal component analysis (PCA), we consider the problem of determining the number of principal components as a model selection prob...
ALT
2010
Springer
13 years 1 months ago
2010
Springer
We focus on the estimation of a probability distribution over a set of trees. We consider here the class of distributions computed by weighted automata - a strict generalization of...
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...
NIPS
2008
13 years 6 months ago
2008
Kernel Principal Component Analysis (KPCA) is a popular generalization of linear PCA that allows non-linear feature extraction. In KPCA, data in the input space is mapped to highe...