Fourier transformation is an extensively studied problem in many research fields. It has
many applications in machine learning, signal processing, compressed sensing, and so on …

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We revisit the classical problem of band-limited signal reconstruction--a variant of the\emph
{Set Query} problem--which asks to efficiently reconstruct (a subset of) a $ d $-dimensional …

Suppose $\mathsf {Est} $ is a randomized estimation algorithm that uses $ n $ random bits
and outputs values in $\mathbb {R}^ d $. We show how to execute $\mathsf {Est} $ on $ k …

Fourier phase retrieval, which seeks to reconstruct a signal from its Fourier magnitude, is of
fundamental importance in fields of engineering and science. In this paper, we give a …

Building on the methods introduced in our recent paper [IK14], we give an algorithm for the
l2/l2 sparse recovery from d-dimensional Fourier measurements that runs in sub-linear time …

We consider the problem of finding the Discrete Fourier Transform (DFT) of N-length signals
with known frequency support of size k. When N is a power of 2 and the frequency support is …

We design a sublinear Fourier sampling algorithm for a case of sparse off-grid frequency
recovery. These are signals with the form f (t)= ∑ _ j= 1^ k a_j e^ i ω _j t+ ∫ ν (ω) e^ i ω td μ …

In this paper we revisit the deterministic version of the Sparse Fourier Transform problem,
which asks to read only a few entries of x∈ ℂⁿ and design a recovery algorithm such that the …

We give an algorithm for ℓ 2/ℓ 2 sparse recovery from Fourier measurements using O (k log
N) samples, matching the lower bound of Do Ba-Indyk-Price-Woodruff'10 for non-adaptive …