Handling ambiguity via input-output kernel learning
Data ambiguities exist in many data mining and machine learning applications such as text categorization and image retrieval. For instance, it is generally beneficial to utilize the ambiguous unlabeled documents to learn a more robust classifier for text categorization under the semi-supervised lear...
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Main Authors: | , , |
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格式: | Conference or Workshop Item |
語言: | English |
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2013
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在線閱讀: | https://hdl.handle.net/10356/99740 http://hdl.handle.net/10220/13014 |
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