Multi-View Local Learning

9 years 1 months ago
Multi-View Local Learning
The idea of local learning, i.e., classifying a particular example based on its neighbors, has been successfully applied to many semi-supervised and clustering problems recently. However, the local learning methods developed so far are all devised for single-view problems. In fact, in many real-world applications, examples are represented by multiple sets of features. In this paper, we extend the idea of local learning to multi-view problem, design a multi-view local model for each example, and propose a Multi-View Local Learning Regularization (MVLL-Reg) matrix. Both its linear and kernel version are given. Experiments are conducted to demonstrate the superiority of the proposed method over several state-of-theart ones.
Dan Zhang, Fei Wang, Changshui Zhang, Tao Li
Added 02 Oct 2010
Updated 02 Oct 2010
Type Conference
Year 2008
Where AAAI
Authors Dan Zhang, Fei Wang, Changshui Zhang, Tao Li
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