421 search results - page 23 / 85 » Reducing Label Complexity by Learning From Bags |
ECCV
2010
Springer
14 years 9 months ago
2010
Springer
Abstract. Multiple-instance learning (MIL) allows for training classifiers from ambiguously labeled data. In computer vision, this learning paradigm has been recently used in many ...
66
Voted
ACL
2009
14 years 7 months ago
2009
Supervised sequence-labeling systems in natural language processing often suffer from data sparsity because they use word types as features in their prediction tasks. Consequently...
88
Voted
LREC
2010
14 years 11 months ago
2010
One of the essential functions of natural language is to talk about spatial relationships between objects. Linguistic constructs can express highly complex, relational structures ...
74
Voted
ICIP
2003
IEEE
15 years 11 months ago
2003
IEEE
Image retrieval with relevance feedback suffers from the small sample problem. Recently, SVM active learning has been proposed to tackle this problem, showing promising results. H...
ICML
2002
IEEE
15 years 10 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...