9 search results - page 1 / 2 » Covariance in Unsupervised Learning of Probabilistic Grammar... |
JMLR
2010
12 years 11 months ago
2010
Probabilistic grammars offer great flexibility in modeling discrete sequential data like natural language text. Their symbolic component is amenable to inspection by humans, while...
ACL
2008
2008
Using Adaptor Grammars to Identify Synergies in the Unsupervised Acquisition of Linguistic Structure
13 years 6 months ago
Adaptor grammars (Johnson et al., 2007b) are a non-parametric Bayesian extension of Probabilistic Context-Free Grammars (PCFGs) which in effect learn the probabilities of entire s...
ACL
2010
13 years 2 months ago
2010
We propose a corpus-based probabilistic framework to extract hidden common syntax across languages from non-parallel multilingual corpora in an unsupervised fashion. For this purp...
JMLR
2010
12 years 11 months ago
2010
Inducing a grammar from text has proven to be a notoriously challenging learning task despite decades of research. The primary reason for its difficulty is that in order to induce...
NIPS
2001
13 years 6 months ago
2001
Unsupervised learning algorithms have been derived for several statistical models of English grammar, but their computational complexity makes applying them to large data sets int...