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Erschienen in:
2013 | OriginalPaper | Buchkapitel
Learning Geometry-Aware Kernels in a Regularization Framework
verfasst von : Binbin Pan, Wen-Sheng Chen
Erschienen in: Computer Analysis of Images and Patterns
Verlag: Springer Berlin Heidelberg
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In this paper, we propose a regularization framework for learning geometry-aware kernels. Some existing geometry-aware kernels can be viewed as instances in our framework. Moreover, the proposed framework can be used as a general platform for developing new geometry-aware kernels. We show how multiple sources of information can be integrated in our framework, allowing us to develop more flexible kernels. We present some new kernels based on our framework. The performance of the kernels is evaluated on classification and clustering tasks. The empirical results show that our kernels significantly improve the performance.