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Semi-supervised learning has received much attention recently. Co-training is a kind of semi-supervised learning method which uses unlabeled data to improve the performance of standard supervised learning algorithms. A novel co-training style algorithm, RASCO (for RAndom Subspace CO-training), is proposed which uses stochastic discrimination theory to extend co-training to multi-view situation. The...
In many practical machine learning fields, obtaining labeled data is hard and expensive. Semi-supervised learning is very useful in these fields since it combines labeled and unlabeled data to boost performance of learning algorithms. Many semi-supervised learning algorithms have been proposed, among which the "co-training" algorithms are widely used. We present a new co-training strategy...
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