129 search results - page 7 / 26 » Active learning with extremely sparse labeled examples |
ICML
2002
IEEE
14 years 8 months ago
2002
IEEE
In a multi-view problem, the features of the domain can be partitioned into disjoint subsets (views) that are sufficient to learn the target concept. Semi-supervised, multi-view a...
ICML
2008
IEEE
14 years 8 months ago
2008
IEEE
Identifying the appropriate kernel function/matrix for a given dataset is essential to all kernel-based learning techniques. A variety of kernel learning algorithms have been prop...
Publication
One of the principal bottlenecks in applying learning techniques to classification problems is the large amount of labeled training data required. Especially for images and video, ...
ICML
2009
IEEE
14 years 8 months ago
2009
IEEE
Dual supervision refers to the general setting of learning from both labeled examples as well as labeled features. Labeled features are naturally available in tasks such as text c...
ALT
2006
Springer
14 years 4 months ago
2006
Springer
Most of the existing active learning algorithms are based on the realizability assumption: The learner’s hypothesis class is assumed to contain a target function that perfectly c...