125 search results - page 19 / 25 » Combining labeled and unlabeled data with word-class distrib... |
101
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WWW
2009
ACM
15 years 10 months ago
2009
ACM
Transferring knowledge from one domain to another is challenging due to a number of reasons. Since both conditional and marginal distribution of the training data and test data ar...
106
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KDD
2009
ACM
15 years 10 months ago
2009
ACM
Active and semi-supervised learning are important techniques when labeled data are scarce. Recently a method was suggested for combining active learning with a semi-supervised lea...
IDEAL
2009
Springer
15 years 4 months ago
2009
Springer
Abstract. Analysis of data without labels is commonly subject to scrutiny by unsupervised machine learning techniques. Such techniques provide more meaningful representations, usef...
109
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NIPS
2004
14 years 11 months ago
2004
Co-training is a method for combining labeled and unlabeled data when examples can be thought of as containing two distinct sets of features. It has had a number of practical succ...
114
Voted
CVPR
2012
IEEE
13 years 2 days ago
2012
IEEE
Active learning aims to reduce the amount of labels required for classification. The main difficulty is to find a good trade-off between exploration and exploitation of the lab...