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AISHIMA Kensuke
Faculty of Computer and Information Sciences Department of Computer Science
Professor
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https://researchmap.jp/aishima
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■ Research Themes
- Unified matrix analysis for strong consistency of estimators based on the singular value decomposition with orthogonal projections for noisy datasets
Kensuke Aishima
Japan Journal of Industrial and Applied Mathematics, 15 Sep. 2025, [Reviewed] - Strong consistency of an estimator by the truncated singular value decomposition for an errors-in-variables regression model with collinearity
Kensuke Aishima
Linear Algebra and its Applications, Jul. 2024, [Reviewed] - Consistent estimation with the use of orthogonal projections for a linear regression model with errors in the variables
Kensuke Aishima
Linear Algebra and its Applications, Mar. 2024, [Reviewed] - Statistical modeling and an adaptive averaging technique for strong convergence of the dynamic mode decomposition.
Kensuke Aishima
Journal of Computational and Applied Mathematics, 2023, [Reviewed] - Strong consistency of the projected total least squares dynamic mode decomposition for datasets with random noise
Kensuke Aishima
Japan Journal of Industrial and Applied Mathematics, 14 Oct. 2022, [Reviewed] - Consistent estimation for an errors-in-variables model based on constrained total least squares problems.
Kensuke Aishima
JSIAM Letters, 2022, [Reviewed] - Convergence proof of the Harmonic Ritz pairs of iterative projection methods with restart strategies for symmetric eigenvalue problems
Kensuke Aishima
JAPAN JOURNAL OF INDUSTRIAL AND APPLIED MATHEMATICS, May 2020, [Reviewed] - Strong convergence for the dynamic mode decomposition based on the total least squares to noisy datasets
Kensuke Aishima
JSIAM LETTERS, 2020, [Reviewed] - Formulations and theorems of quadratically convergent methods for inverse symmetric eigenvalue problems
Kensuke Aishima
IEICE NONLINEAR THEORY AND ITS APPLICATIONS, 2020, [Reviewed] - Iterative refinement for singular value decomposition based on matrix multiplication.
Takeshi Ogita; Kensuke Aishima
J. Comput. Appl. Math., 2020, [Reviewed] - A quadratically convergent algorithm for inverse generalized eigenvalue problems.
Kensuke Aishima
J. Comput. Appl. Math., 2020, [Reviewed] - Iterative refinement for symmetric eigenvalue decomposition II: clustered eigenvalues
Takeshi Ogita; Kensuke Aishima
JAPAN JOURNAL OF INDUSTRIAL AND APPLIED MATHEMATICS, Jul. 2019, [Reviewed] - Iterative refinement for symmetric eigenvalue decomposition
Takeshi Ogita; Kensuke Aishima
JAPAN JOURNAL OF INDUSTRIAL AND APPLIED MATHEMATICS, Nov. 2018, [Reviewed] - A quadratically convergent algorithm for inverse eigenvalue problems with multiple eigenvalues
Kensuke Aishima
Linear Algebra and Its Applications, 15 Jul. 2018, [Reviewed] - A quadratically convergent algorithm based on matrix equations for inverse eigenvalue problems
Kensuke Aishima
Linear Algebra and Its Applications, 01 Apr. 2018, [Reviewed] - Extension of an error analysis of the randomized Kaczmarz method for inconsistent linear systems.
Yushi Morijiri; Kensuke Aishima; Takayasu Matsuo
JSIAM Lett., 2018, [Reviewed] - On convergence of iterative projection methods for symmetric eigenvalue problems
Kensuke Aishima
JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS, Feb. 2017, [Reviewed] - Global convergence of the restarted Lanczos and Jacobi-Davidson methods for symmetric eigenvalue problems
Kensuke Aishima
NUMERISCHE MATHEMATIK, Nov. 2015, [Reviewed] - A note on the convergence theorem of the tridiagonal QR algorithm with Wilkinson's shift
Kensuke Aishima
JAPAN JOURNAL OF INDUSTRIAL AND APPLIED MATHEMATICS, Jul. 2015, [Reviewed] - A note on convergence and a posteriori error estimates of the classical Jacobi method
Tsuchiya Takuya; Aishima Kensuke
IEICE NONLINEAR THEORY AND ITS APPLICATIONS, 2015, [Reviewed] - Orthogonal polynomial approach to estimation of poles of rational functions from data on open curves
Shinji Ito; Kensuke Aishima; Takaaki Nara; Masaaki Sugihara
JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS, Jan. 2015, [Reviewed] - A note on the Rayleigh quotient iteration for symmetric eigenvalue problems
Kensuke Aishima
JAPAN JOURNAL OF INDUSTRIAL AND APPLIED MATHEMATICS, Nov. 2014, [Reviewed] - A shift strategy for superquadratic convergence in the dqds algorithm for singular values
Kensuke Aishima; Takayasu Matsuo; Kazuo Murota; Masaaki Sugihara
JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS, Feb. 2014, [Reviewed] - A Wilkinson-like multishift QR algorithm for symmetric eigenvalue problems and its global convergence
Kensuke Aishima; Takayasu Matsuo; Kazuo Murota; Masaaki Sugihara
JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS, Sep. 2012, [Reviewed] - dqds WITH AGGRESSIVE EARLY DEFLATION
Yuji Nakatsukasa; Kensuke Aishima; Ichitaro Yamazaki
SIAM JOURNAL ON MATRIX ANALYSIS AND APPLICATIONS, 2012, [Reviewed] - A note on the dqds algorithm with Rutishauser's shift for singular values
Kensuke Aishima; Takayasu Matsuo; Kazuo Murota
JAPAN JOURNAL OF INDUSTRIAL AND APPLIED MATHEMATICS, 2011, [Reviewed] - Superquadratic convergence of DLASQ for computing matrix singular values
Kensuke Aishima; Takayasu Matsuo; Kazuo Murota; Masaaki Sugihara
JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS, Jun. 2010, [Reviewed] - A survey on convergence theorems of the dqds algorithm for computing singular values
Kensuke Aishima; Takayasu Matsuo; Kazuo Murota; Masaaki Sugihara
Journal of Math-for-Industry, 2010, [Reviewed] - Rigorous proof of cubic convergence for the dqds algorithm for singular values
Kensuke Aishima; Takayasu Matsuo; Kazuo Murota
JAPAN JOURNAL OF INDUSTRIAL AND APPLIED MATHEMATICS, Feb. 2008, [Reviewed] - Superquadratically Convergent Shift Strategy with Theoretical Guarantee in the dqds Algorithm for Singular Values(Theory)
Aishima Kensuke; Matsuo Takayasu; Murota Kazuo; Sugihara Masaaki
Transactions of the Japan Society for Industrial and Applied Mathematics, 2008, [Reviewed] - ON CONVERGENCE OF THE DQDS ALGORITHM FOR SINGULAR VALUE COMPUTATION
Kensuke Aishima; Takayasu Matsuo; Kazuo Murota; Masaaki Sugihara
SIAM JOURNAL ON MATRIX ANALYSIS AND APPLICATIONS, 2008, [Reviewed] - On Convergence of dqds and mdLVs Algorithms for Singular Value Computation(Theory)
Aishima Kensuke; Matsuo Takayasu; Murota Kazuo; Sugihara Masaaki
Transactions of the Japan Society for Industrial and Applied Mathematics, 2007, [Reviewed]
- Fundamental Theory of a Singular Value Algorithm : Convergence Analysis of the dqds Algorithm
Aishima Kensuke
Bulletin of the Japan Society for Industrial and Applied Mathematics, 2012 - JSIAM Seminar(Conference Reports)
Aishima Kensuke; Matsuo Takayasu
Bulletin of the Japan Society for Industrial and Applied Mathematics, 2010 - SIAM CSE09(Conference Reports)
Katagiri Takahiro; Aishima Kensuke; Nakajima Kengo
Bulletin of the Japan Society for Industrial and Applied Mathematics, 2009 - Convergence Theorems of the dpds Algorithm for Singular Values (High Performance Algorithms for Computational Science and Their Applications)
Aishima Kensuke; Matsuo Takayasu; Murota Kazuo; Sugihara Masaaki
RIMS Kokyuroku, Oct. 2008 - On Convergence of the dqds and mdLVs Algorithms for Computing Matrix Singular Values(Mathematical Sciences for Large Scale Numerical Simulations)
Aishima Kensuke; Matsuo Takayasu; Murota Kazuo
RIMS Kokyuroku, Nov. 2007
■ Research Themes
- Development of new efficient structure-preserving numerical methods based on model reductions
Grant-in-Aid for Scientific Research (B)
The University of Tokyo
01 Apr. 2017 - 31 Mar. 2021 - Fast numerical algorithms for singular value decompositions
Grant-in-Aid for Young Scientists (B)
The University of Tokyo
01 Apr. 2013 - 31 Mar. 2018 - Fast algorithm of the singular value decomposition
Grant-in-Aid for Research Activity Start-up
The University of Tokyo
24 Aug. 2011 - 31 Mar. 2013
