Unsupervised Learning Using the Tensor Voting Graph

DOI10.1007/978-3-319-18461-6_23zbMath1451.62034OpenAlexW2227619225MaRDI QIDQ3300307

Gérard Medioni, Shay Deutsch

Publication date: 28 July 2020

Published in: Lecture Notes in Computer Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-319-18461-6_23

zbMATH Keywords

manifold learningtensor votingintersecting manifolds

Mathematics Subject Classification ID

Directional data; spatial statistics (62H11) Statistics on manifolds (62R30) Nonparametric estimation (62G05) Learning and adaptive systems in artificial intelligence (68T05)

Related Items (1)

Learning the geometric structure of manifolds with singularities using the tensor voting graph

Cites Work

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• Finding the homology of submanifolds with high confidence from random samples
• Vector diffusion maps and the connection Laplacian
• Geometric diffusions as a tool for harmonic analysis and structure definition of data: Diffusion maps
• Principal Manifolds and Nonlinear Dimensionality Reduction via Tangent Space Alignment
• Laplacian Eigenmaps for Dimensionality Reduction and Data Representation
• Hessian eigenmaps: Locally linear embedding techniques for high-dimensional data

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