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154
Voted
EMMCVPR
1999
Springer
15 years 8 months ago
1999
Springer
This paper considers the use of the EM-algorithm, combined with mean field theory, for parameter estimation in Markov random field models from unlabelled data. Special attention ...
153
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KDD
2010
ACM
15 years 7 months ago
2010
ACM
In this paper we propose a novel algorithm for multi-task learning with boosted decision trees. We learn several different learning tasks with a joint model, explicitly addressing...
151
Voted
ECCV
2010
Springer
15 years 8 months ago
2010
Springer
Sparse coding of sensory data has recently attracted notable attention in research of learning useful features from the unlabeled data. Empirical studies show that mapping the data...
173
Voted
JMLR
2012
13 years 6 months ago
2012
Reducing the number of labeled examples required to learn accurate prediction models is an important problem in structured output prediction. In this paper we propose a new transd...
141
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SAC
2009
ACM
15 years 10 months ago
2009
ACM
Incorporating background knowledge into data mining algorithms is an important but challenging problem. Current approaches in semi-supervised learning require explicit knowledge p...