2015 | OriginalPaper | Buchkapitel
A Local Method for Canonical Correlation Analysis
verfasst von : Tengju Ye, Zhipeng Xie, Ang Li
Erschienen in: Natural Language Processing and Chinese Computing
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Canonical Correlation Analysis (CCA) is a standard statistical technique for finding linear projections of two arbitrary vectors that are maximally correlated. In complex situations, the linearity of CCA is not applicable. In this paper, we propose a novel local method for CCA to handle the non-linear situations.We aim to find a series of local linear projections instead of a single globe one. We evaluate the performance of our method and CCA on two real-world datasets. Our experiments show that local method outperforms original CCA in several realistic cross-modal multimedia retrieval tasks.