Contributions to Unsupervised and Semi-Supervised Learning
This thesis studies two problems in theoretical machine learning. The first part of the thesis investigates the statistical stability of clustering algorithms. In the second part, we study the relative advantage of having unlabeled data in classification problems. Clustering stability was proposed...
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| Language: | en |
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2009
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| Online Access: | http://hdl.handle.net/10012/4445 |