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A Local Method for Canonical Correlation Analysis

  • Tengju YeEmail author
  • Zhipeng Xie
  • Ang Li
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9362)

Absract

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.

Keywords

Local linearity Multivariate analysis Cross-modal multimedia retrieval 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.School of Computer ScienceFudan UniversityShanghaiChina

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