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KDD
2009
ACM
227views Data Mining» more  KDD 2009»
16 years 7 months ago
Efficiently learning the accuracy of labeling sources for selective sampling
Many scalable data mining tasks rely on active learning to provide the most useful accurately labeled instances. However, what if there are multiple labeling sources (`oracles...
Pinar Donmez, Jaime G. Carbonell, Jeff Schneider
IJCAI
2007
15 years 8 months ago
Detection of Cognitive States from fMRI Data Using Machine Learning Techniques
Over the past decade functional Magnetic Resonance Imaging (fMRI) has emerged as a powerful technique to locate activity of human brain while engaged in a particular task or cogni...
Vishwajeet Singh, Krishna P. Miyapuram, Raju S. Ba...
JCNS
2000
78views more  JCNS 2000»
15 years 6 months ago
Computational Consequences of Temporally Asymmetric Learning Rules: II. Sensory Image Cancellation
Abstract. The electrosensory lateral line lobe (ELL) of mormyridelectric sh is a cerebellum-likestructure that receives primarya erent input from electroreceptors in the skin. Purk...
Patrick D. Roberts, Curtis C. Bell
ECTEL
2009
Springer
16 years 1 months ago
A New Framework for Dynamic Adaptations and Actions
Adaptive course generation is more flexible if it includes mechanisms deciding just-in-time which exercises, which external resources, and which tools to include for an individual...
Carsten Ullrich, Tianxiang Lu, Erica Melis
ICTAI
2008
IEEE
16 years 29 days ago
LRNPlanner: Planning Personalized and Contextualized E-Learning Routes
The aim of educational systems is to design a sequence of learning objects on a set of topics tailored to the learner’s goals and individual properties. However, some of the mai...
Eva Onaindia, Antonio Garrido, Oscar Sapena