1174 search results - page 26 / 235 » Boosting for transfer learning |
CORR
2011
Springer
14 years 1 months ago
2011
Springer
Boosting is a popular way to derive powerful learners from simpler hypothesis classes. Following previous work (Mason et al., 1999; Friedman, 2000) on general boosting frameworks,...
ICML
2004
IEEE
15 years 10 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...
ALT
2007
Springer
15 years 4 months ago
2007
Springer
In transfer learning the aim is to solve new learning tasks using fewer examples by using information gained from solving related tasks. Existing transfer learning methods have be...
EUROCOLT
1995
Springer
15 years 1 months ago
1995
Springer
k. The model we study can be interpreted as a broad, abstract extension of the well-studied on-line prediction model to a general decision-theoretic setting. We show that the multi...
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ML
2012
ACM
13 years 5 months ago
2012
ACM
Dependency networks approximate a joint probability distribution over multiple random variables as a product of conditional distributions. Relational Dependency Networks (RDNs) are...