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We prove lower bounds for the smallest singular value of rectangular, multivariate Vandermonde matrices with nodes on the complex unit circle. The nodes are ``off the grid'', groups of nodes cluster, and the studied minimal singular value…

Numerical Analysis · Mathematics 2019-07-17 Stefan Kunis , Dominik Nagel

We study the problem of super-resolution of a linear combination of Dirac distributions and their derivatives on a one-dimensional circle from noisy Fourier measurements. Following numerous recent works on the subject, we consider the…

Numerical Analysis · Mathematics 2023-03-21 Dmitry Batenkov , Nuha Diab

We consider the inverse problem of recovering the locations and amplitudes of a collection of point sources represented as a discrete measure, given $M+1$ of its noisy low-frequency Fourier coefficients. Super-resolution refers to a stable…

Information Theory · Computer Science 2022-10-17 Weilin Li , Wenjing Liao

We prove upper and lower bounds for the spectral condition number of rectangular Vandermonde matrices with nodes on the complex unit circle. The nodes are "off the grid", pairs of nodes nearly collide, and the studied condition number grows…

Numerical Analysis · Mathematics 2019-10-23 Stefan Kunis , Dominik Nagel

We study rectangular Vandermonde matrices $\mathbf{V}$ with $N+1$ rows and $s$ irregularly spaced nodes on the unit circle, in cases where some of the nodes are "clustered" together -- the elements inside each cluster being separated by at…

Numerical Analysis · Mathematics 2020-07-27 Dmitry Batenkov , Benedikt Diederichs , Gil Goldman , Yosef Yomdin

We derive bounds on the extremal singular values and the condition number of NxK, with N>=K, Vandermonde matrices with nodes in the unit disk. The mathematical techniques we develop to prove our main results are inspired by a link---first…

Information Theory · Computer Science 2017-08-07 Céline Aubel , Helmut Bölcskei

Following recent interest by the community, the scaling of the minimal singular value of a Vandermonde matrix with nodes forming clusters on the length scale of Rayleigh distance on the complex unit circle is studied. Using approximation…

Numerical Analysis · Mathematics 2021-07-27 Dmitry Batenkov , Gil Goldman

We consider the problem of stable recovery of sparse signals of the form $$F(x)=\sum_{j=1}^d a_j\delta(x-x_j),\quad x_j\in\mathbb{R},\;a_j\in\mathbb{C}, $$ from their spectral measurements, known in a bandwidth $\Omega$ with absolute error…

Numerical Analysis · Mathematics 2020-01-27 Dmitry Batenkov , Gil Goldman , Yosef Yomdin

Suppose that a solution $\widetilde{\mathbf{x}}$ to an underdetermined linear system $\mathbf{b} = \mathbf{A} \mathbf{x}$ is given. $\widetilde{\mathbf{x}}$ is approximately sparse meaning that it has a few large components compared to…

Information Theory · Computer Science 2015-06-29 Mohammadreza Malek-Mohammadi , Cristian R. Rojas , Magnus Jansson , Massoud Babaie-Zadeh

We give degree lower bounds for quotient line bundles of the lowest piece of a Hodge module induced by a complex variation of Hodge structures outside a simple normal crossing divisor, beyond the unipotent variation case. This note aims to…

Algebraic Geometry · Mathematics 2026-05-14 Ze Yun

A problem of paramount importance in both pure (Restricted Invertibility problem) and applied mathematics (Feature extraction) is the one of selecting a submatrix of a given matrix, such that this submatrix has its smallest singular value…

Machine Learning · Computer Science 2018-04-05 Stephane Chretien , Zhen-Wai Olivier Ho

We consider the problem of locating a signal whose frequencies are "off grid" and clustered in a narrow band. Given noisy sample access to a function $g(t)$ with Fourier spectrum in a narrow range $[f_0 - \Delta, f_0 + \Delta]$, how…

Data Structures and Algorithms · Computer Science 2019-05-01 Xue Chen , Eric Price

The objective of this paper is to understand the superlinear convergence behavior of the GMRES method when the coefficient matrix has clustered eigenvalues. In order to understand the phenomenon, we analyze the convergence using the…

Numerical Analysis · Mathematics 2025-04-25 Zeyu Liao , Ken Hayami

We consider the problem of robustly recovering a $k$-sparse coefficient vector from the Fourier series that it generates, restricted to the interval $[- \Omega, \Omega]$. The difficulty of this problem is linked to the superresolution…

Information Theory · Computer Science 2015-02-06 Laurent Demanet , Nam Nguyen

The discrete Fourier transform matrix is one of the most important matrices in linear algebra, and submatrices of it arise in a variety of applications. Though the discrete Fourier transform matrix is unitary, its submatrices can be…

Numerical Analysis · Mathematics 2026-04-30 Rikhav Shah , John Urschel

We study the fundamental problem of clustering $n$ points into $K$ groups drawn from a mixture of isotropic Gaussians in $\mathbb{R}^d$. Specifically, we investigate the requisite minimal distance $\Delta$ between mean vectors to partially…

Statistics Theory · Mathematics 2026-02-27 Alexandra Carpentier , Nicolas Verzelen

This paper studies the extreme singular values of non-harmonic Fourier matrices. Such a matrix of size $m\times s$ can be written as $\Phi=[ e^{-2\pi i j x_k}]_{j=0,1,\dots,m-1, k=1,2,\dots,s}$ for some set $\mathcal{X}=\{x_k\}_{k=1}^s$.…

Numerical Analysis · Mathematics 2024-10-01 Weilin Li

This paper considers the problem of clustering a partially observed unweighted graph---i.e., one where for some node pairs we know there is an edge between them, for some others we know there is no edge, and for the remaining we do not know…

Machine Learning · Computer Science 2014-07-25 Yudong Chen , Ali Jalali , Sujay Sanghavi , Huan Xu

The submodular partitioning problem asks to minimize, over all partitions $P$ of a ground set $V$, the sum of a given submodular function $f$ over the parts of $P$. The problem has seen considerable work in approximability, as it…

Data Structures and Algorithms · Computer Science 2025-07-03 Kristóf Bérczi , Karthekeyan Chandrasekaran , Tamás Király , Daniel P. Szabo

Super-resolution is the problem of recovering a superposition of point sources using bandlimited measurements, which may be corrupted with noise. This signal processing problem arises in numerous imaging problems, ranging from astronomy to…

Machine Learning · Computer Science 2015-09-29 Qingqing Huang , Sham M. Kakade
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