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» Electronic case studies: a problem-based learning approach
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DATAMINE
2010
161views more  DATAMINE 2010»
14 years 11 months ago
Predicting labels for dyadic data
: In dyadic prediction, the input consists of a pair of items (a dyad), and the goal is to predict the value of an observation related to the dyad. Special cases of dyadic predicti...
Aditya Krishna Menon, Charles Elkan
CVPR
2008
IEEE
16 years 3 months ago
Semi-supervised SVM batch mode active learning for image retrieval
Active learning has been shown as a key technique for improving content-based image retrieval (CBIR) performance. Among various methods, support vector machine (SVM) active learni...
Steven C. H. Hoi, Rong Jin, Jianke Zhu, Michael R....
ICALT
2005
IEEE
15 years 7 months ago
Collaborative Virtual Environment Technology for People with Autism
This paper focuses on an investigation of Collaborative Virtual Environment (CVE) technology for people with autism, paying particular attention to the use of avatar representatio...
Yufang Cheng, David J. Moore, Paul McGrath, Yulei ...
UAI
1997
15 years 3 months ago
Sequential Update of Bayesian Network Structure
There is an obvious need for improving the performance and accuracy of a Bayesian network as new data is observed. Because of errors in model construction and changes in the dynam...
Nir Friedman, Moisés Goldszmidt
VIS
2009
IEEE
399views Visualization» more  VIS 2009»
16 years 3 months ago
Visual Human+Machine Learning
In this paper we describe a novel method to integrate interactive visual analysis and machine learning to support the insight generation of the user. The suggested approach combine...
Raphael Fuchs, Jürgen Waser, Meister Eduard GrÃ...