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NIPS
1994
14 years 11 months ago
Efficient Methods for Dealing with Missing Data in Supervised Learning
We present efficient algorithms for dealing with the problem of missing inputs (incomplete feature vectors) during training and recall. Our approach is based on the approximation ...
Volker Tresp, Ralph Neuneier, Subutai Ahmad
ICASSP
2010
IEEE
14 years 10 months ago
Weakly supervised learning with decision trees applied to fisheries acoustics
This paper addresses the training of classification trees for weakly labelled data. We call ”weakly labelled data”, a training set such as the prior labelling information pro...
Riwal Lefort, Ronan Fablet, Jean-Marc Boucher
FOCM
2006
65views more  FOCM 2006»
14 years 9 months ago
Approximation Methods for Supervised Learning
Let be an unknown Borel measure defined on the space Z := X
Ronald A. DeVore, Gerard Kerkyacharian, Dominique ...
INFORMATICASI
2008
46views more  INFORMATICASI 2008»
14 years 9 months ago
A Readability Checker with Supervised Learning Using Deep Indicators
Tim vor der Brück, Sven Hartrumpf, Hermann He...