502 search results - page 1 / 101 » Learning from General Label Constraints |
SSPR
2004
Springer
13 years 9 months ago
2004
Springer
Most machine learning algorithms are designed either for supervised or for unsupervised learning, notably classification and clustering. Practical problems in bioinformatics and i...
SIGIR
2008
ACM
13 years 4 months ago
2008
ACM
It is difficult to apply machine learning to new domains because often we lack labeled problem instances. In this paper, we provide a solution to this problem that leverages domai...
ICCV
2007
IEEE
14 years 6 months ago
2007
IEEE
In this paper, we take the human age and pose estimation problems as examples to study automatic designing regressor from training samples with uncertain nonnegative labels. First...
JMLR
2010
12 years 11 months ago
2010
In this paper, we present an overview of generalized expectation criteria (GE), a simple, robust, scalable method for semi-supervised training using weakly-labeled data. GE fits m...
MM
2006
ACM
13 years 10 months ago
2006
ACM
Labeling objects in images is an essential prerequisite for many visual learning and recognition applications that depend on training data, such as image retrieval, object detecti...