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 …

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 …

In this paper, we consider the extensively studied problem of computing a k-sparse
approximation to the d-dimensional Fourier transform of a length n signal. Our algorithm …

We study the problem of interpolating a noisy Fourier-sparse signal in the time duration 0,T
from noisy samples in the same range, where the ground truth signal can be any k-Fourier …

In recent years, a number of works have studied methods for computing the Fourier
transform in sublinear time if the output is sparse. Most of these have focused on the discrete …

In the last decade a broad literature has arisen studying sparse recovery, the estimation of
sparse vectors from low dimensional linear projections. Sparse recovery has a wide variety …

In this paper, a sublinear time algorithm is presented for the reconstruction of functions that
can be represented by just few out of a potentially large candidate set of Fourier basis …

(MATH) We give an algorithm for finding a Fourier representation R of B terms for a given
discrete signal signal A of length N, such that ‖\signal-\repn‖_2^2 is within the factor (1+ ε) …

Reconstructing continuous signals based on a small number of discrete samples is a
fundamental problem across science and engineering. We are often interested in signals …

The ability to resolve detail in the object that is being imaged, named by resolution, is the
core parameter of an imaging system. Super-resolution is a class of techniques that can …