358 search results - page 4 / 72 » Learning from labeled and unlabeled data on a directed graph |
ICML
2002
IEEE
14 years 9 months ago
2002
IEEE
Supervised learning techniques for text classi cation often require a large number of labeled examples to learn accurately. One way to reduce the amountoflabeled datarequired is t...
KDD
2008
ACM
14 years 9 months ago
2008
ACM
Active learning may hold the key for solving the data scarcity problem in supervised learning, i.e., the lack of labeled data. Indeed, labeling data is a costly process, yet an ac...
NIPS
2007
13 years 10 months ago
2007
Semi-supervised methods use unlabeled data in addition to labeled data to construct predictors. While existing semi-supervised methods have shown some promising empirical performa...
BMCBI
2010
13 years 8 months ago
2010
Background: Extracting protein-protein interactions from biomedical literature is an important task in biomedical text mining. Supervised machine learning methods have been used w...
COLING
2008
13 years 10 months ago
2008
In this paper, we focus on the adaptation problem that has a large labeled data in the source domain and a large but unlabeled data in the target domain. Our aim is to learn relia...