Nonlinear dimensionality reduction by topologically constrained isometric embedding

DOI10.1007/s11263-010-0322-1zbMath1477.68489OpenAlexW2167769608MaRDI QIDQ408807

Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel, Guy Rosman

Publication date: 12 April 2012

Published in: International Journal of Computer Vision (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11263-010-0322-1

zbMATH Keywords

differential geometrymachine learningdimensionality reductionIsomapimage manifolds

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Computer graphics; computational geometry (digital and algorithmic aspects) (68U05) Differential geometric aspects of statistical manifolds and information geometry (53B12)

Related Items (8)

Multi-manifold discriminant Isomap for visualization and classification ⋮ LRA: local rigid averaging of stretchable non-rigid shapes ⋮ Novel parameter-free and parametric same degree distribution-based dimensionality reduction algorithms for trustworthy data structure preserving ⋮ Reconstruction and interpolation of manifolds. I: The geometric Whitney problem ⋮ Diffusion pruning for rapidly and robustly selecting global correspondences using local isometry ⋮ Spectral multidimensional scaling ⋮ Densifying distance spaces for shape and image retrieval ⋮ Parallel Transport Unfolding: A Connection-Based Manifold Learning Approach

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