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2009
Springer

When Semi-supervised Learning Meets Ensemble Learning

9 years 6 months ago
When Semi-supervised Learning Meets Ensemble Learning
Abstract. Semi-supervised learning and ensemble learning are two important learning paradigms. The former attempts to achieve strong generalization by exploiting unlabeled data; the latter attempts to achieve strong generalization by using multiple learners. In this paper we advocate generating stronger learning systems by leveraging unlabeled data and classifier combination.
Zhi-Hua Zhou
Added 20 May 2010
Updated 20 May 2010
Type Conference
Year 2009
Where MCS
Authors Zhi-Hua Zhou
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