Active Learning in Parallel Universes


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CEBRON, Nicolas, Michael BERTHOLD, 2010. Active Learning in Parallel Universes. the 19th ACM international conference. Toronto, ON, Canada, 26. Okt 2010 - 30. Okt 2010. In: Proceedings of the 19th ACM international conference on Information and knowledge management - CIKM '10. New York, New York, USA:ACM Press, pp. 1621-1624. ISBN 978-1-4503-0099-5. Available under: doi: 10.1145/1871437.1871688

@inproceedings{Cebron2010Activ-24312, title={Active Learning in Parallel Universes}, year={2010}, doi={10.1145/1871437.1871688}, isbn={978-1-4503-0099-5}, address={New York, New York, USA}, publisher={ACM Press}, booktitle={Proceedings of the 19th ACM international conference on Information and knowledge management - CIKM '10}, pages={1621--1624}, author={Cebron, Nicolas and Berthold, Michael} }

Active Learning in Parallel Universes 2010 CIKM'10 : proceedings of the 19th International Conference on Information & Knowledge Management and Co-Located Workshops; Oktober 26 - 30, 2010, Toronto, Ontario, Canada / ed. by Xiangji Jimmy Huang .... - New York, N.Y. : ACM, Association for Computing Machinery, 2010. - S. 1621-1624. - ISBN 978-1-4503-0099-5 This work addresses two challenges in combination: learning with a very limited number of labeled training examples (active learning) and learning in the presence of multiple views for each object where the global model to be learned is spread out over some or all of these views (learning in parallel universes). We propose a new active learning approach which selects the best samples to query the label with the goal of improving overall model accuracy and determining which universe contributes most to the local model. The resulting combination and class-specific weighting of universes provides a significantly better classification accuracy than traditional active learning methods. Cebron, Nicolas 2013-08-23T12:28:44Z Berthold, Michael 2013-08-23T12:28:44Z Berthold, Michael Cebron, Nicolas eng terms-of-use

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