86 search results - page 7 / 18 » Learning stick-figure models using nonparametric Bayesian pr... |
ACL
2010
14 years 7 months ago
2010
Learning a tree substitution grammar is very challenging due to derivational ambiguity. Our recent approach used a Bayesian non-parametric model to induce good derivations from tr...
159
click to vote
ICML
2010
IEEE
14 years 10 months ago
2010
IEEE
The hierarchical Dirichlet process (HDP) is a Bayesian nonparametric mixed membership model--each data point is modeled with a collection of components of different proportions. T...
75
Voted
ACL
2008
2008
Using Adaptor Grammars to Identify Synergies in the Unsupervised Acquisition of Linguistic Structure
14 years 11 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...
NIPS
2001
14 years 11 months ago
2001
Statistical learning and probabilistic inference techniques are used to infer the hand position of a subject from multi-electrode recordings of neural activity in motor cortex. Fi...
JMLR
2010
14 years 4 months ago
2010
Deep belief networks are a powerful way to model complex probability distributions. However, it is difficult to learn the structure of a belief network, particularly one with hidd...