141 search results - page 7 / 29 » Learning r-of-k Functions by Boosting |
ICS
2010
Tsinghua U.
14 years 4 months ago
2010
Tsinghua U.
We consider the problem of boosting the accuracy of weak learning algorithms in the agnostic learning framework of Haussler (1992) and Kearns et al. (1992). Known algorithms for t...
CVPR
2004
IEEE
14 years 8 months ago
2004
IEEE
Image retrieval critically relies on the distance function used to compare a query image to images in the database. We suggest to learn such distance functions by training binary ...
CVPR
2008
IEEE
14 years 8 months ago
2008
IEEE
The required amount of labeled training data for object detection and classification is a major drawback of current methods. Combining labeled and unlabeled data via semisupervise...
CORR
2011
Springer
12 years 10 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
14 years 7 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...