A generalized diffusion frame for parsimonious representation of functions on data defined manifolds

DOI10.1016/j.neunet.2010.12.007zbMath1222.42036OpenAlexW2025362507WikidataQ33818944 ScholiaQ33818944MaRDI QIDQ553271

Hrushikesh N. Mhaskar

Publication date: 26 July 2011

Published in: Neural Networks (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.neunet.2010.12.007

zbMATH Keywords

Littlewood-Paley decompositiondata defined manifoldsdiffusion waveletskernel based methodslocal Besov spaces

Mathematics Subject Classification ID

Nontrigonometric harmonic analysis involving wavelets and other special systems (42C40) Learning and adaptive systems in artificial intelligence (68T05)

Related Items

Smooth function extension based on high dimensional unstructured data, Representation of functions on big data associated with directed graphs, Local Approximation Using Hermite Functions, Metric entropy, \(n\)-widths, and sampling of functions on manifolds, Local approximation of operators, Data Based Construction of Kernels for Classification, Approximate Quadrature Measures on Data-Defined Spaces, A unified framework for harmonic analysis of functions on directed graphs and changing data, A direct approach for function approximation on data defined manifolds, Representation of functions on big data: graphs and trees

Uses Software

• OPQ

Cites Work

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