421 search results - page 6 / 85 » Reducing Label Complexity by Learning From Bags |
109
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AAAI
2007
14 years 12 months ago
2007
Multi-label learning deals with ambiguous examples each may belong to several concept classes simultaneously. In this learning framework, the inherent ambiguity of each example is...
ICASSP
2010
IEEE
14 years 9 months ago
2010
IEEE
The goal of semi-supervised image segmentation is to obtain the segmentation from a partially labeled image. By utilizing the image manifold structure in labeled and unlabeled pix...
111
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CVPR
2012
IEEE
13 years 6 hour ago
2012
IEEE
Multiple Instance Learning (MIL) has been widely exploited in many computer vision tasks, such as image retrieval, object tracking and so on. To handle ambiguity of instance label...
125
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KDD
2012
ACM
13 years 11 hour ago
2012
ACM
Multi-instance multi-label learning (MIML) is a framework for supervised classification where the objects to be classified are bags of instances associated with multiple labels....
ICML
2010
IEEE
14 years 10 months ago
2010
IEEE
We propose a max-margin formulation for the multi-label classification problem where the goal is to tag a data point with a set of pre-specified labels. Given a set of L labels, a...