1364 search results - page 161 / 273 » Sampling Methods for Unsupervised Learning |
112
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ECML
2005
Springer
15 years 8 months ago
2005
Springer
Active selection of good training examples is an important approach to reducing data-collection costs in machine learning; however, most existing methods focus on maximizing classi...
111
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PAKDD
2004
ACM
15 years 8 months ago
2004
ACM
The use of unlabeled data to aid classification is important as labeled data is often available in limited quantity. Instead of utilizing training samples directly into semi-super...
105
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LREC
2008
15 years 4 months ago
2008
One problem of data-driven answer extraction in open-domain factoid question answering is that the class distribution of labeled training data is fairly imbalanced. This imbalance...
109
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NAACL
2007
15 years 4 months ago
2007
We propose a new framework for supervised machine learning. Our goal is to learn from smaller amounts of supervised training data, by collecting a richer kind of training data: an...
115
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JMLR
2010
14 years 9 months ago
2010
We present a continuous time Bayesian network reasoning and learning engine (CTBN-RLE). A continuous time Bayesian network (CTBN) provides a compact (factored) description of a co...