[Updated on Apr. 18] Integration of CiNii Articles into CiNii Research

Predicting the convergence of BiCG method from grayscale matrix images

  • Ota Ryo
    Graduate School of Library, Information and Media Studies, University of Tsukuba
  • Hasegawa Hidehiko
    Faculty of Library, Information and Media Science, University of Tsukuba


<p> The convergence of the BiConjugate Gradient (BiCG) method depends on its input matrices. We tried to predict the convergence of BiCG method by applying a Convolutional Neural Network to matrices that had been converted to grayscale images. Using 875 real non-symmetric matrices in the SuiteSparse Matrix Collection, we applied the 5-fold cross-validation method and were able to predict convergence with an average accuracy that exceeded 80\% for all cases in the test collection. </p>


  • JSIAM Letters

    JSIAM Letters 12 (0), 45-48, 2020

    The Japan Society for Industrial and Applied Mathematics


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