69 search results - page 11 / 14 » Learning online discussion structures by conditional random ... |
JMLR
2010
13 years 2 months ago
2010
Composite likelihood methods provide a wide spectrum of computationally efficient techniques for statistical tasks such as parameter estimation and model selection. In this paper,...
ACL
2012
11 years 10 months ago
2012
This paper presents a novel sequence labeling model based on the latent-variable semiMarkov conditional random fields for jointly extracting argument roles of events from texts. ...
NIPS
2008
13 years 9 months ago
2008
Abstract: Structure learning of dynamic Bayesian networks provide a principled mechanism for identifying conditional dependencies in time-series data. This learning procedure assum...
FOIKS
2008
Springer
14 years 4 months ago
2008
Springer
Supervised learning deals with the inference of a distribution over an output or label space $\CY$ conditioned on points in an observation space $\CX$, given a training dataset $D$...
ICDM
2007
IEEE
14 years 1 months ago
2007
IEEE
This paper addresses the issue of extraction of an academic researcher social network. By researcher social network extraction, we are aimed at finding, extracting, and fusing the...