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General numerical methods
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New applications of matrix methods
N. L. Zamarashkin, I. V. Oseledets, E. E. Tyrtyshnikov
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691–695 |
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Algebras closed by $J$-hermitianity in displacement formulas
E. Bozzo, P. Deidda, C. di Fiore
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696–705 |
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An accurate restarting for shift-and-invert Кrylov subspaces computing matrix exponential actions of nonsymmetric matrices
M. A. Botchev
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706–722 |
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A survey of Shanks' extrapolation methods and their applications
C. Brezinski, M. Redivo-Zaglia
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723–743 |
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Inductive matrix completion with feature selection
M. Burkina, I. Nazarov, M. Panov, G. Fedonin, B. Shirokikh
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744–758 |
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Computing the eigenvectors of nonsymmetric tridiagonal matrices
P. Van Dooren, T. Laudadio, N. Mastronardi
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759–775 |
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TT ranks of approximate tensorizations of some smooth functions
L. I. Vysotsky
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776–786 |
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New algorithms for solving nonlinear eigenvalue problems
W. Gander
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787–799 |
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Reduced-order modeling of deep neural networks
J. V. Gusak, T. K. Daulbaev, I. V. Oseledets, E. S. Ponomarev, A. S. Cichocki
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800–812 |
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On the accuracy of cross and column low-rank MaxVol approximations in average
N. L. Zamarashkin, A. I. Osinskii
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813–826 |
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Low-rank approximation algorithms for matrix completion with random sampling
O. S. Lebedeva, A. I. Osinskii, S. V. Petrov
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827–844 |
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Structuring data with block term decomposition: decomposition of joint tensors and variational block term decomposition as a parametrized mixture distribution model
I. V. Oseledets, P. V. Kharyuk
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845–864 |
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Optimal control
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TT-QI: Faster value iteration in tensor train format for stochastic optimal control
A. I. Boyko, I. V. Oseledets, G. Ferrer
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865–877 |
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Partial Differential Equations
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Numerical method for solving volume integral equations on a nonuniform grid
A. B. Samokhin, E. E. Tyrtyshnikov
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878–884 |
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Mathematical physics
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Extraction of inductances and spatial distributions of currents in a model of superconducting neuron
S. V. Bakurskiy, N. V. Klenov, M. Yu. Kupriyanov, I. I. Soloviev, M. M. Khapaev
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885–894 |
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Prospects of tensor-based numerical modeling of the collective electrostatics in many-particle systems
V. Kh. Khoromskaia, B. N. Khoromsky
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895 |
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Computer science
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Overview of visualization methods for artificial neural networks
S. A. Matveev, I. V. Oseledets, E. S. Ponomarev, A. V. Chertkov
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896–910 |
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