1837 search results - page 55 / 368 » Learning From Ambiguous Examples |
191
Voted
CVPR
2009
IEEE
16 years 11 months ago
2009
IEEE
Multi-instance multi-label learning (MIML) refers to the
learning problems where each example is represented by a
bag/collection of instances and is labeled by multiple labels.
...
148
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CVPR
2012
IEEE
13 years 7 months ago
2012
IEEE
Identifying suitable image features is a central challenge in computer vision, ranging from representations for lowlevel to high-level vision. Due to the difficulty of this task,...
200
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KDD
2012
ACM
13 years 7 months 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....
170
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AAAI
2006
15 years 5 months ago
2006
The ability to interpret demonstrations from the perspective of the teacher plays a critical role in human learning. Robotic systems that aim to learn effectively from human teach...
124
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FLAIRS
2006
15 years 5 months ago
2006
Learning tasks from a single demonstration presents a significant challenge because the observed sequence is inherently an incomplete representation of the procedure that is speci...