@inproceedings{4d9d1a1b695e43fdb64167019b8e31c8,
title = "Multiscale manifold representation and modeling",
abstract = "Many real world data sets can be viewed as points in a higher-dimensional space that lie concentrated around a lower-dimensional manifold structure. We propose a new multiscale representation for such point clouds based on lifting and perfect matching. The result is an adaptive wavelet transform that decomposes a point cloud into manifold approximations and details at multiple scales. We illustrate with several examples that the transform can extract an unknown smooth manifold from noisy point cloud samples using simple wavelet thresholding ideas.",
author = "Hyeokho Choi and Richard Baraniuk",
note = "Copyright: Copyright 2020 Elsevier B.V., All rights reserved.; 2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05 ; Conference date: 18-03-2005 Through 23-03-2005",
year = "2005",
doi = "10.1109/ICASSP.2005.1416072",
language = "English (US)",
isbn = "0780388747",
series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "569--572",
booktitle = "2005 IEEE ICASSP '05 - Proc. - Design and Implementation of Signal Proces.Syst.,Indust. Technol. Track,Machine Learning for Signal Proces. Signal Proces. Education, Spec. Sessions",
address = "United States",
}