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ICML
2006
IEEE
14 years 10 months ago
Efficient learning of Naive Bayes classifiers under class-conditional classification noise
We address the problem of efficiently learning Naive Bayes classifiers under classconditional classification noise (CCCN). Naive Bayes classifiers rely on the hypothesis that the ...
Christophe Nicolas Magnan, François Denis, ...
ICML
2007
IEEE
14 years 10 months ago
Self-taught learning: transfer learning from unlabeled data
We present a new machine learning framework called "self-taught learning" for using unlabeled data in supervised classification tasks. We do not assume that the unlabele...
Rajat Raina, Alexis Battle, Honglak Lee, Benjamin ...
CHI
2010
ACM
14 years 4 months ago
Examining multiple potential models in end-user interactive concept learning
End-user interactive concept learning is a technique for interacting with large unstructured datasets, requiring insights from both human-computer interaction and machine learning...
Saleema Amershi, James Fogarty, Ashish Kapoor, Des...
AIA
2007
13 years 11 months ago
Classification of biomedical high-resolution micro-CT images for direct volume rendering
This paper introduces a machine learning approach into the process of direct volume rendering of biomedical highresolution 3D images. More concretely, it proposes a learning pipel...
Maite López-Sánchez, Jesús Ce...
ICML
2003
IEEE
14 years 10 months ago
Semi-Supervised Learning of Mixture Models
This paper analyzes the performance of semisupervised learning of mixture models. We show that unlabeled data can lead to an increase in classification error even in situations wh...
Fabio Gagliardi Cozman, Ira Cohen, Marcelo Cesar C...