LPGraph-package: Nonparametric Smoothing of Laplacian Graph Spectra
In LPGraph: Nonparametric Smoothing of Laplacian Graph Spectra
Description
Author(s)
References
Description
This package provides an algorithm to approximate and smooth the Laplacian graph spectra of a network with ordered vertices using LP-nonparametric basis. The underlying theory yields a reduced order (compressive) characterization of spectral graph properties.
Author(s)
Mukhopadhyay, S. and Wang, K.
Maintainer: Kaijun Wang <kaijun.wang@temple.edu>
References
Mukhopadhyay, S. and Wang, K. (2018), "Graph Spectral Compression via Smoothing".
Mukhopadhyay, S. (2017+), "Unified Statistical Theory of Spectral Graph Analysis".
Mukhopadhyay, S. and Parzen, E. (2014), "LP Approach to Statistical Modeling", arXiv:1405.2601.
LPGraph documentation built on Jan. 31, 2020, 1:06 a.m.
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Description Author(s) References
Description
This package provides an algorithm to approximate and smooth the Laplacian graph spectra of a network with ordered vertices using LP-nonparametric basis. The underlying theory yields a reduced order (compressive) characterization of spectral graph properties.
Author(s)
Mukhopadhyay, S. and Wang, K.
Maintainer: Kaijun Wang <kaijun.wang@temple.edu>
References
Mukhopadhyay, S. and Wang, K. (2018), "Graph Spectral Compression via Smoothing".
Mukhopadhyay, S. (2017+), "Unified Statistical Theory of Spectral Graph Analysis".
Mukhopadhyay, S. and Parzen, E. (2014), "LP Approach to Statistical Modeling", arXiv:1405.2601.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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