13 search results - page 1 / 3 » Accelerated training of conditional random fields with stoch... |
ICML
2006
IEEE
14 years 6 months ago
2006
IEEE
We apply Stochastic Meta-Descent (SMD), a stochastic gradient optimization method with gain vector adaptation, to the training of Conditional Random Fields (CRFs). On several larg...
ICDM
2007
IEEE
13 years 7 months ago
2007
IEEE
For applications with consecutive incoming training examples, on-line learning has the potential to achieve a likelihood as high as off-line learning without scanning all availabl...
JMLR
2008
13 years 5 months ago
2008
Log-linear and maximum-margin models are two commonly-used methods in supervised machine learning, and are frequently used in structured prediction problems. Efficient learning of...
ICML
2004
IEEE
14 years 6 months ago
2004
IEEE
Conditional Random Fields (CRFs; Lafferty, McCallum, & Pereira, 2001) provide a flexible and powerful model for learning to assign labels to elements of sequences in such appl...
ECML
2006
Springer
13 years 9 months ago
2006
Springer
Abstract. Conditional Random Fields (CRFs) provide a powerful instrument for labeling sequences. So far, however, CRFs have only been considered for labeling sequences over flat al...