Novel parameter-free and parametric same degree distribution-based dimensionality reduction algorithms for trustworthy data structure preserving

DOI10.1016/j.ins.2023.120030OpenAlexW4390079542MaRDI QIDQ6126848

Guillaume Gilloppe, Baptiste Sivy, Da-Qing Chen, Laureta Hajderanj, Sandra Dudley

Publication date: 10 April 2024

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ins.2023.120030

zbMATH Keywords

high dimensional datacomputational timedimensionality reduction techniquesstructure capturing

Mathematics Subject Classification ID

Biology and other natural sciences (92-XX) Computer science (68-XX)

Cites Work

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• Nonlinear dimensionality reduction by topologically constrained isometric embedding
• Diffusion maps
• Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis
• Reducing the Dimensionality of Data with Neural Networks
• Principal Manifolds and Nonlinear Dimensionality Reduction via Tangent Space Alignment
• Hessian eigenmaps: Locally linear embedding techniques for high-dimensional data

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