Results 21 to 30 of about 535,226 (278)
Coarse-Grained Pruning of Neural Network Models Based on Blocky Sparse Structure
Entropy, 2021 Deep neural networks may achieve excellent performance in many research fields. However, many deep neural network models are over-parameterized. The computation of weight matrices often consumes a lot of time, which requires plenty of computing resources.
Lan Huang +5 more
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Conditioning analysis of block incomplete factorization and its application to elliptic equations [PDF]
, 1997 The paper deals with eigenvalue estimates for block incomplete fac- torization methods for symmetric matrices. First, some previous results on upper bounds for the maximum eigenvalue of preconditioned matrices are generalized to each eigenvalue.
Axelsson, Owe, Lu, Hao
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Deficiency Indices of Block Jacobi Matrices: Survey
Современная математика: Фундаментальные направления, 2021 The paper is a survey and concerns with infinite symmetric block Jacobi matrices J with m×m-matrix entries. We discuss several results on general block Jacobi matrices to be either self-adjoint or have maximal as well as intermediate deficiency indices ...
Viktoriya S. Budyka +2 more
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The norm of polynomials in large random and deterministic matrices [PDF]
, 2011 Let X_N= (X_1^(N), ..., X_p^(N)) be a family of N-by-N independent, normalized random matrices from the Gaussian Unitary Ensemble. We state sufficient conditions on matrices Y_N =(Y_1^(N), ..., Y_q^(N)), possibly random but independent of X_N, for which ...
Male, C.
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Block LU factorizations of M-matrices [PDF]
Numerische Mathematik, 1998 It is well known that any nonsingular M-matrix admits an LU factorization into M-matrices (with L and U lower and upper triangular respectively) and any singular M-matrix is permutation similar to an M-matrix which admits an LU factorization into M-matrices.
McDonald, J. J., Schneider, H.
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The Electronic Journal of Linear Algebra, 2007 In this paper, block distance matrices are introduced. Suppose F is a square block matrix in which each block is a symmetric matrix of some given order. If F is positive semidefinite, the block distance matrix D is defined as a matrix whose (i, j)-block is given by D ij = F ii +F jj -2F ij .
R. Balaji, Ravindra Bapat
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On the Limiting Distribution of the Spectra of Random Block Matrices
MathematicsThe behavior of the spectra of symmetric block-type random matrices with symmetric blocks of high dimensionality is considered in this paper. Under minimal conditions regarding the distributions of matrix block elements (Lindeberg conditions), the ...
Alexander N. Tikhomirov
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Block-encoding structured matrices for data input in quantum computing [PDF]
QuantumThe cost of data input can dominate the run-time of quantum algorithms. Here, we consider data input of arithmetically structured matrices via $\textit{block encoding}$ circuits, the input model for the quantum singular value transform and related ...
Christoph Sünderhauf +2 more
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Applied Sciences, 2022 The sparse matrix–vector product (SpMV), considered one of the seven dwarfs (numerical methods of significance), is essential in high-performance real-world scientific and analytical applications requiring solution of large sparse linear equation systems,
Muhammad Ahmed +6 more
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Algebraic and toroidal representation of the genetic code
Frontiers in Applied Mathematics and StatisticsThe genetic code is a set of regulatory principles that control the translation of information encoded in messenger RNA (mRNA) into a sequence of amino acids.
Rodrigo Rodríguez-Gutiérrez +3 more
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