Predicting the convergence of BiCG method from grayscale matrix images
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- Ota Ryo
- Graduate School of Library, Information and Media Studies, University of Tsukuba
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- Hasegawa Hidehiko
- Faculty of Library, Information and Media Science, University of Tsukuba
Description
<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>
Journal
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- JSIAM Letters
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JSIAM Letters 12 (0), 45-48, 2020
The Japan Society for Industrial and Applied Mathematics
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Details 詳細情報について
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- CRID
- 1390566775155781120
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- NII Article ID
- 130007881798
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- ISSN
- 18830617
- 18830609
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- Text Lang
- en
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- Data Source
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- JaLC
- Crossref
- CiNii Articles
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- Abstract License Flag
- Disallowed