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Numerical Methods for the Genvar Criterion of Multiple-Sets Canonical Analysis

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Abstract

The Genvar criterion, proposed by Steel, is one of the important generalizations of canonical correlation analysis. This paper deals with iterative methods for the Genvar criterion. An alternating variable method is analysed and an inexact version of it is proposed. Two starting point strategies are suggested to enhance these iterative algorithms. Numerical results show that, these starting point strategies not only can improve the rate of convergence, but also boost up the probability of finding a global solution.

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Acknowledgments

We are very grateful to both referees for their constructive comments and suggestions.

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Authors and Affiliations

  1. School of Mathematical Sciences, Ocean University of China, Qingdao, 266003, China

    Xinguo Liu & Jianping You

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  1. Xinguo Liu
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  2. Jianping You
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Correspondence to Jianping You.

Additional information

This work was partially supported by NSF of China, Grant 11371333.

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Liu, X., You, J. Numerical Methods for the Genvar Criterion of Multiple-Sets Canonical Analysis. J Sci Comput 67, 821–835 (2016). https://doi.org/10.1007/s10915-015-0103-7

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