Titlebook: Machine Learning and Knowledge Discovery in Databases; European Conference, Walter Daelemans,Bart Goethals,Katharina Morik Conference proce

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Conference proceedings 2008in Antwerp, Belgium, in September 2008. The 100 papers presented in two volumes, together with 5 invited talks, were carefully reviewed and selected from 521 submissions. In addition to the regular papers the volume contains 14 abstracts of papers appearing in full version in the Machine Learning Jo

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Kernel-Based Inductive Transfer the new data. The criterion is based on a meta kernel capturing the similarity of two datasets. In experiments on small molecule and text data, kernel-based inductive transfer showed a statistically significant improvement over the best individual kernel in almost all cases.

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Improving Classification with Pairwise Constraints: A Margin-Based Approachse constraints into the conventional margin-based learning framework. We also present an efficient algorithm, PCSVM, to solve the pairwise constraint learning problem. Experiments with 15 data sets show that pairwise constraint information significantly increases the performance of classification.