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IEEEICCI
2009
IEEE
14 years 11 months ago
Learning from an ensemble of Receptive Fields
Abstract-In this paper, we construct a neural-inspired computational model based on the representational capabilities of receptive fields. The proposed model, known as Shape Encodi...
Hanlin Goh, Joo Hwe Lim, Chai Quek
CVPR
2011
IEEE
14 years 10 months ago
Learning the Easy Things First: Self-Paced Visual Category Discovery
Objects vary in their visual complexity, yet existing discovery methods perform “batch” clustering, paying equal attention to all instances simultaneously—regardless of the ...
Yong Jae Lee, Kristen Grauman
COGSCI
2010
85views more  COGSCI 2010»
15 years 2 months ago
The Effects of Feature-Label-Order and Their Implications for Symbolic Learning
Symbols enable people to organize and communicate about the world. However, the ways in which symbolic knowledge is learned and then represented in the mind are poorly understood....
Michael Ramscar, Daniel Yarlett, Melody Dye, Katie...
KDD
2012
ACM
238views Data Mining» more  KDD 2012»
13 years 4 months ago
Multi-source learning for joint analysis of incomplete multi-modality neuroimaging data
Incomplete data present serious problems when integrating largescale brain imaging data sets from different imaging modalities. In the Alzheimer’s Disease Neuroimaging Initiativ...
Lei Yuan, Yalin Wang, Paul M. Thompson, Vaibhav A....
AIED
2011
Springer
14 years 5 months ago
Early Prediction of Cognitive Tool Use in Narrative-Centered Learning Environments
Narrative-centered learning environments introduce novel opportunities for supporting student problem solving and learning. By incorporating cognitive tools into plots and characte...
Lucy R. Shores, Jonathan P. Rowe, James C. Lester