Spectral multidimensional scaling

DOI10.1073/pnas.1308708110zbMath1292.62078arXiv1311.2187OpenAlexW2078047215WikidataQ37318157 ScholiaQ37318157MaRDI QIDQ5170977

Yonathan Aflalo, Ron Kimmel

Publication date: 25 July 2014

Published in: Proceedings of the National Academy of Sciences (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1311.2187

Mathematics Subject Classification ID

Directional data; spatial statistics (62H11) Learning and adaptive systems in artificial intelligence (68T05) Spectral theory; eigenvalue problems on manifolds (58C40)

Related Items (5)

On the Optimality of Shape and Data Representation in the Spectral Domain ⋮ On convex relaxation of graph isomorphism ⋮ Non-rigid Shape Correspondence Using Surface Descriptors and Metric Structures in the Spectral Domain ⋮ Making sense of big data ⋮ Curvature in image and shape processing

Cites Work

• Nonlinear dimensionality reduction by topologically constrained isometric embedding
• A linear-space algorithm for distance preserving graph embedding
• Embedding Riemannian manifolds by their heat kernel
• Diffusion maps
• Multigrid multidimensional scaling
• Computing geodesic paths on manifolds
• Hessian eigenmaps: Locally linear embedding techniques for high-dimensional data
• Ramifications, old and new, of the eigenvalue problem

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