Sciweavers

MCS
2009
Springer

When Semi-supervised Learning Meets Ensemble Learning

13 years 10 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
Comments (0)