@inbook{8f1da375ff7f46fc85411ff2f2fcaf54,
title = "Harmonic analysis of databases and matrices",
abstract = "We describe methods to organize and process matrices/databases through a bi-multiscale tensor product harmonic Analysis on row and column functions. The goal is to reorganize the matrix so that its entries exhibit smoothness or predictability relative to the tensor row column geometry. In particular we show that approximate bi-Holder smoothness follows from simple l p entropy conditions. We describe various applications both for the analysis of matrices of linear transformations, as well for the extraction of information and structure in document databases.",
keywords = "Bi-Holder, Databases, Diffusion geometry, Machine learning, Partition trees, Tensor Haar, Tensor harmonic Analysis",
author = "Coifman, {Ronald R.} and Matan Gavish",
note = "Publisher Copyright: {\textcopyright} Springer Science+Business Media New York 2013.",
year = "2013",
doi = "10.1007/978-0-8176-8376-4_15",
language = "الإنجليزيّة",
series = "Applied and Numerical Harmonic Analysis",
number = "9780817683757",
pages = "297--310",
booktitle = "Applied and Numerical Harmonic Analysis",
edition = "9780817683757",
}