Grassmannian Diffusion Maps--Based Dimension Reduction and Classification for High-Dimensional Data

DOI10.1137/20M137001XzbMath1489.53136MaRDI QIDQ5065498

Dimitrios G. Giovanis, Michael D. Shields, Ketson R. M. dos Santos

Publication date: 22 March 2022

Published in: SIAM Journal on Scientific Computing (Search for Journal in Brave)

zbMATH Keywords

dimension reductionGrassmann manifoldface recognitiondiffusion mapsdata classification

Mathematics Subject Classification ID

Applications of Markov chains and discrete-time Markov processes on general state spaces (social mobility, learning theory, industrial processes, etc.) (60J20) Grassmannians, Schubert varieties, flag manifolds (14M15) Spaces of embeddings and immersions (58D10) Local Riemannian geometry (53B20) Manifolds of mappings (58D15) Methods of local Riemannian geometry (53B21) Applications of differential geometry to data and computer science (53Z50)

Related Items (3)

Data-driven uncertainty quantification in computational human head models ⋮ A survey of unsupervised learning methods for high-dimensional uncertainty quantification in black-box-type problems ⋮ AI‐enhanced iterative solvers for accelerating the solution of large‐scale parametrized systems

Uses Software

• t-SNE

Cites Work

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