Three lectures on Fourier analysis and learning theory

Fuente: arXiv
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Main Author: Zhang, Haonan
Format: Preprint
Published: 2024
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author Zhang, Haonan
author_facet Zhang, Haonan
contents Fourier analysis on the discrete hypercubes $\{-1,1\}^n$ has found numerous applications in learning theory. A recent breakthrough involves the use of a classical result from Fourier analysis, the Bohnenblust--Hille inequality, in the context of learning low-degree Boolean functions. In these lecture notes, we explore this line of research and discuss recent progress in discrete quantum systems and classical Fourier analysis.
format Preprint
id arxiv_https___arxiv_org_abs_2409_10886
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Three lectures on Fourier analysis and learning theory
Zhang, Haonan
Functional Analysis
Mathematical Physics
Classical Analysis and ODEs
Fourier analysis on the discrete hypercubes $\{-1,1\}^n$ has found numerous applications in learning theory. A recent breakthrough involves the use of a classical result from Fourier analysis, the Bohnenblust--Hille inequality, in the context of learning low-degree Boolean functions. In these lecture notes, we explore this line of research and discuss recent progress in discrete quantum systems and classical Fourier analysis.
title Three lectures on Fourier analysis and learning theory
topic Functional Analysis
Mathematical Physics
Classical Analysis and ODEs
url https://arxiv.org/abs/2409.10886