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Three lectures on Fourier analysis and learning theory

Published 17 Sep 2024 in math.FA, math-ph, math.CA, and math.MP | (2409.10886v1)

Abstract: 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.

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