Results 11 to 20 of about 870,005 (280)
Optimal CUR Matrix Decompositions [PDF]
Proceedings of the forty-sixth annual ACM symposium on Theory of computing, 2014 The CUR decomposition of an $m \times n$ matrix $A$ finds an $m \times c$ matrix $C$ with a subset of $c < n$ columns of $A,$ together with an $r \times n$ matrix $R$ with a subset of $r < m$ rows of $A,$ as well as a $c \times r$ low-rank matrix $U ...
Boutsidis C. +4 more
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Singular-Value-Decomposition-Based Matrix Surgery
EntropyThis paper is motivated by the need to stabilise the impact of deep learning (DL) training for medical image analysis on the conditioning of convolution filters in relation to model overfitting and robustness.
Jehan Ghafuri, Sabah Jassim
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Randomized Matrix Decompositions Using R [PDF]
Journal of Statistical Software, 2019 Matrix decompositions are fundamental tools in the area of applied mathematics, statistical computing, and machine learning. In particular, low-rank matrix decompositions are vital, and widely used for data analysis, dimensionality reduction, and data ...
N. Benjamin Erichson +3 more
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Mueller matrix differential decomposition [PDF]
Optics Letters, 2011 We present a Mueller matrix decomposition based on the differential formulation of the Mueller calculus. The differential Mueller matrix is obtained from the macroscopic matrix through an eigenanalysis. It is subsequently resolved into the complete set of 16 differential matrices that correspond to the basic types of optical behavior for depolarizing ...
Ortega-Quijano, Noé +1 more
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Probability Matrix Decomposition Models [PDF]
Psychometrika, 1996 In this paper, we consider a class of models for two-way matrices with binary entries of 0 and 1. First, we consider Boolean matrix decomposition, conceptualize it as a latent response model (LRM) and, by making use of this conceptualization, generalize it to a larger class of matrix decomposition models.
Maris, E., DeBoeck, P., Mechelen, I. van
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Two New Matrix Classes Related to the CMP Inverse: CMP and Co-CMP Matrices
Mathematics, 2023 This paper focuses on two new matrix classes related to the CMP inverse of a square matrix, called the CMP and co-CMP matrices. Some of their characterizations are identified based on the core-EP decomposition and subspace operations.
Yinlan Chen, Jiale Gao, Kezheng Zuo
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IEEE Access, 2022 In this paper, in order to improve the reliability of Multi-User Multiple-Input Multiple-Output Visible Light Communication (MU-MIMO-VLC) system, we propose a precoding scheme that based on Singular Value Decomposition (SVD) and Geometric Mean ...
Wenduo Qiu, Yan Feng, You Zhang
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Rank-Sparsity Incoherence for Matrix Decomposition [PDF]
, 2009 Suppose we are given a matrix that is formed by adding an unknown sparse matrix to an unknown low-rank matrix. Our goal is to decompose the given matrix into its sparse and low-rank components.
Chandrasekaran, Venkat +3 more
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Mean-field density matrix decompositions [PDF]
The Journal of Chemical Physics, 2020 We introduce new and robust decompositions of mean-field Hartree–Fock and Kohn–Sham density functional theory relying on the use of localized molecular orbitals and physically sound charge population protocols. The new lossless property decompositions, which allow for partitioning one-electron reduced density matrices into either bond-wise or atomic ...
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Constructive quantum scaling of unitary matrices [PDF]
, 2016 In this work we present a method of decomposition of arbitrary unitary matrix $U\in\mathbf U(2^k)$ into a product of single-qubit negator and controlled-$\sqrt{\mbox{NOT}}$ gates.
Glos, Adam, Sadowski, Przemysław
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