154 search results - page 14 / 31 » Maximum Entropy Model Learning of the Translation Rules |
CVPR
2000
IEEE
15 years 11 months ago
2000
IEEE
?Gibbsian fields or Markov random fields are widely used in Bayesian image analysis, but learning Gibbs models is computationally expensive. The computational complexity is pronoun...
NIPS
2000
14 years 10 months ago
2000
The principle of maximizing mutual information is applied to learning overcomplete and recurrent representations. The underlying model consists of a network of input units driving...
COLING
2000
14 years 10 months ago
2000
This paper describes a self-modelling, incremental algorithm for learning translation rules from existing bilingual corpora. The notions of supracontext and subcontext are extende...
ICML
2001
IEEE
15 years 10 months ago
2001
IEEE
We present conditional random fields, a framework for building probabilistic models to segment and label sequence data. Conditional random fields offer several advantages over hid...
TCBB
2010
14 years 7 months ago
2010
—Gene expression data usually contain a large number of genes, but a small number of samples. Feature selection for gene expression data aims at finding a set of genes that best...