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» A Framework for Multiple-Instance Learning
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121
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CHI
2006
ACM
16 years 4 months ago
Embedded phenomena: supporting science learning with classroom-sized distributed simulations
`Embedded phenomena' is a learning technology framework in which simulated scientific phenomena are mapped onto the physical space of classrooms. Students monitor and control...
Tom Moher
143
Voted
PERCOM
2007
ACM
16 years 3 months ago
Structural Learning of Activities from Sparse Datasets
Abstract. A major challenge in pervasive computing is to learn activity patterns, such as bathing and cleaning from sensor data. Typical sensor deployments generate sparse datasets...
Fahd Albinali, Nigel Davies, Adrian Friday
191
Voted
CVPR
2010
IEEE
16 years 9 hour ago
Learning Full Pairwise Affinities for Spectral Segmentation
This paper studies the problem of learning a full range of pairwise affinities gained by integrating local grouping cues for spectral segmentation. The overall quality of the spect...
Tae Hoon Kim (Seoul National University), Kyoung M...
116
Voted
ICASSP
2009
IEEE
15 years 10 months ago
Connecting spectral and spring methods for manifold learning
Diffusion Maps (DiffMaps) has recently provided a general framework that unites many other spectral manifold learning algorithms, including Laplacian Eigenmaps, and it has become ...
Shannon M. Hughes, Peter J. Ramadge
121
Voted
ICRA
2009
IEEE
111views Robotics» more  ICRA 2009»
15 years 10 months ago
Interactive learning of the acoustic properties of household objects
— Human beings can perceive object properties such as size, weight, and material type based solely on the sounds that the objects make when an action is performed on them. In ord...
Jivko Sinapov, Mark Wiemer, Alexander Stoytchev