750 search results - page 45 / 150 » Learning SVMs from Sloppily Labeled Data |
AAAI
2000
13 years 10 months ago
2000
Due to the large variation and richness of visual inputs, statistical learning gets more and more concerned in the practice of visual processing such as visual tracking and recogn...
ACL
2008
13 years 10 months ago
2008
We present a novel semi-supervised training algorithm for learning dependency parsers. By combining a supervised large margin loss with an unsupervised least squares loss, a discr...
TAL
2010
Springer
13 years 7 months ago
2010
Springer
This paper shows how the best data-driven dependency parsers available today [1] can be improved by learning from unlabeled data. We focus on German and Swedish and show that label...
CVPR
2011
IEEE
13 years 27 days ago
2011
IEEE
We consider a special type of multi-label learning where class assignments of training examples are incomplete. As an example, an instance whose true class assignment is (c1, c2, ...
PAMI
2012
11 years 11 months ago
2012
—Cross-domain learning methods have shown promising results by leveraging labeled patterns from the auxiliary domain to learn a robust classifier for the target domain which has ...