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169
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CVPR
2009
IEEE
16 years 9 months ago
Learning a Distance Metric from Multi-instance Multi-label Data
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. ...
Rong Jin (Michigan State University), Shijun Wang...
CVPR
2012
IEEE
13 years 5 months ago
Learning rotation-aware features: From invariant priors to equivariant descriptors
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,...
Uwe Schmidt, Stefan Roth
177
Voted
KDD
2012
ACM
205views Data Mining» more  KDD 2012»
13 years 5 months ago
Rank-loss support instance machines for MIML instance annotation
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....
Forrest Briggs, Xiaoli Z. Fern, Raviv Raich
155
Voted
AAAI
2006
15 years 3 months ago
Perspective Taking: An Organizing Principle for Learning in Human-Robot Interaction
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...
Matt Berlin, Jesse Gray, Andrea Lockerd Thomaz, Cy...
FLAIRS
2006
15 years 3 months ago
One-Shot Procedure Learning from Instruction and Observation
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...
Hyuckchul Jung, James F. Allen, Nathanael Chambers...