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Published in 2018 at "Ecology"
DOI: 10.1002/ecy.2469
Abstract: Eigenvector-mapping methods such as Moran's eigenvector maps (MEM) are derived from a spatial weighting matrix (SWM) that describes the relations among a set of sampled sites. The specification of the SWM is a crucial step,…
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Keywords:
spatial weighting;
weighting matrix;
swm;
eigenvector ... See more keywords
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Published in 2021 at "Probability Theory and Related Fields"
DOI: 10.1007/s00440-021-01062-4
Abstract: In this paper, we study the random matrix model of Gaussian Unitary Ensemble (GUE) with fixed-rank (aka spiked) external source. We will focus on the critical regime of the Baik–Ben Arous–Péché (BBP) phase transition and…
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Keywords:
bbp;
critical regime;
distribution;
transition ... See more keywords
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Published in 2020 at "Signal, Image and Video Processing"
DOI: 10.1007/s11760-019-01604-3
Abstract: Classical supervised feature extraction methods, such as linear discriminant analysis (LDA) and nonparametric weighted feature extraction (NWFE), and search for projection directions through which the ratio of a between-class scatter matrix to a within-class scatter…
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Keywords:
extraction;
image;
classification;
eigenvector ... See more keywords
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Published in 2024 at "Communications Physics"
DOI: 10.1038/s42005-023-01504-6
Abstract: Signed network embedding methods allow for a low-dimensional representation of nodes and primarily focus on partitioning the graph into clusters, hence losing information on continuous node attributes. Here, we introduce a spectral embedding algorithm for…
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Keywords:
eigenvector embedding;
eigenvector;
sheep signed;
hamiltonian eigenvector ... See more keywords
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3
Published in 2023 at "Proceedings of the National Academy of Sciences of the United States of America"
DOI: 10.1073/pnas.2207046120
Abstract: Significance Eigenvectors are used throughout the physical and social sciences to reduce the dimension of complex problems to manageable levels and to distinguish signal from noise. Our research identifies and mitigates bias in the leading…
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Keywords:
finance;
james stein;
leading eigenvector;
stein leading ... See more keywords
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Published in 2024 at "Molecular Physics"
DOI: 10.1080/00268976.2024.2307498
Abstract: Kassman’s path deletion procedure for the determination of eigenvector polynomials (EPs) and hence the eigenvector or molecular orbital (MO) coefficients of a molecular graph is revisited with required proofs and illustrations. As EPs vanish for…
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Keywords:
eigenvector;
deletion procedure;
path deletion;
procedure ... See more keywords
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Published in 2022 at "IEEE Signal Processing Letters"
DOI: 10.1109/lsp.2022.3205274
Abstract: The dominant eigenvector of the covariance matrix of a zero-mean data distribution describes the line wherein the variance of the projected data is maximized. In practical applications, the true covariance matrix is unknown and its…
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Keywords:
elliptical distributions;
covariance matrix;
pca;
eigenvector ... See more keywords
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Published in 2022 at "Journal of Healthcare Engineering"
DOI: 10.1155/2022/5625897
Abstract: The proposed Edge-based Trust Management System (E-TMS) uses an Eigenvector-based approach for eliminating the security threats present in the Internet of Things (IoT) enabled smart city environment. In most existing trust management systems, the trust…
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Keywords:
system;
trust;
eigenvector;
trust management ... See more keywords
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1
Published in 2022 at "PLoS ONE"
DOI: 10.1371/journal.pone.0274567
Abstract: Ranking user reputation and object quality in online rating systems is of great significance for the construction of reputation systems. In this paper we put forward an iterative algorithm for ranking reputation and quality in…
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Keywords:
user reputation;
converging reputation;
reputation;
eigenvector ... See more keywords
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Published in 2020 at "Frontiers of biogeography"
DOI: 10.21425/f5fbg47295
Abstract: Macroecological data are usually structured in space, so taking into account spatial autocorrelation in regression and correlation analyses is essential for a better understanding of patterns and processes. Many methods are available to deal with…
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Keywords:
analyses large;
variance partitioning;
spatial autocorrelation;
eigenvector ... See more keywords