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We prove that a set of finite perimeter is indecomposable if and only if it is, up to a choice of suitable representative, connected in the 1-fine topology. This gives a topological characterization of indecomposability which is new even in…

Metric Geometry · Mathematics 2025-12-23 Paolo Bonicatto , Panu Lahti , Enrico Pasqualetto

In electrical impedance tomography, algorithms based on minimizing a linearized residual functional have been widely used due to their flexibility and good performance in practice. However, no rigorous convergence results have been…

Analysis of PDEs · Mathematics 2018-10-11 Bastian Harrach , Mach Nguyet Minh

The problem of recovering a structured signal from its linear measurements in the presence of speckle noise is studied. This problem appears in many imaging systems such as synthetic aperture radar and optical coherence tomography. The…

Information Theory · Computer Science 2021-08-03 Wenda Zhou , Shirin Jalali , Arian Maleki

We introduce a new ``Winding Number Conjecture'' about maps from the $(d-1)$-skeleton of the $((d+1)(q-1))$-simplex into $\real^d$. This conjecture is equivalent to the Topological Tverberg Theorem. Furthermore, many statements about the…

Combinatorics · Mathematics 2007-05-23 Torsten Schöneborn

We initiate the study of the shortest reconfiguration problem for independent sets under the adjacency relation derived from the independent set polytope. Given a graph and two independent sets, the problem asks for a shortest sequence…

Data Structures and Algorithms · Computer Science 2026-04-28 Jean Cardinal , Kevin Mann , Akira Suzuki , Takahiro Suzuki , Yuma Tamura , Xiao Zhou

Let $K\subset\mathbb R^d$ be a compact subset equipped with a $\delta$-Ahlfors regular measure $\mu$. For any $\tau>1/d$ and any ``inhomogeneous'' vector $\boldsymbol{\theta}\in\mathbb R^d$, let $W_d(\psi_\tau,\boldsymbol{\theta})$ denote…

Number Theory · Mathematics 2026-02-17 Yubin He , Lingmin Liao

We investigate the sample size requirement for exact recovery of a high order tensor of low rank from a subset of its entries. In the Tucker decomposition framework, we show that the Riemannian optimization algorithm with initial value…

Machine Learning · Statistics 2019-11-13 Jian-Feng Cai , Lizhang Miao , Yang Wang , Yin Xian

Experimental design is a classical statistics problem and its aim is to estimate an unknown $m$-dimensional vector $\beta$ from linear measurements where a Gaussian noise is introduced in each measurement. For the combinatorial experimental…

Machine Learning · Statistics 2024-12-06 Mohit Singh , Weijun Xie

A starting point in the investigation of intersecting systems of subsets of a finite set is the elementary observation that the size of a family of pairwise intersecting subsets of a finite set [n]={1,...,n}, denoted by 2^{[n]}, is at most…

Combinatorics · Mathematics 2017-03-03 Eva Czabarka , Glenn Hurlbert , Vikram Kamat

In this paper we consider the problem of reconstructing an image that is downsampled in the space of its $SE(2)$ wavelet transform, which is motivated by classical models of simple cells receptive fields and feature preference maps in…

Numerical Analysis · Mathematics 2021-10-05 Davide Barbieri

A coreset (or core-set) of an input set is its small summation, such that solving a problem on the coreset as its input, provably yields the same result as solving the same problem on the original (full) set, for a given family of problems…

Machine Learning · Computer Science 2019-10-22 Ibrahim Jubran , Alaa Maalouf , Dan Feldman

We consider the problem of recovering an unknown effectively $(s_1,s_2)$-sparse low-rank-$R$ matrix $X$ with possibly non-orthogonal rank-$1$ decomposition from incomplete and inaccurate linear measurements of the form $y = \mathcal A (X) +…

Numerical Analysis · Mathematics 2020-07-29 Massimo Fornasier , Johannes Maly , Valeriya Naumova

This paper introduces the Reed Muller Sieve, a deterministic measurement matrix for compressed sensing. The columns of this matrix are obtained by exponentiating codewords in the quaternary second order Reed Muller code of length $N$. For…

Information Theory · Computer Science 2010-04-20 Robert Calderbank , Stephen Howard , Sina Jafarpour

Reconstructing a signal on a graph from observations on a subset of the vertices is a fundamental problem in the field of graph signal processing. It is often assumed that adding additional observations to an observation set will reduce the…

Signal Processing · Electrical Eng. & Systems 2023-07-04 Baskaran Sripathmanathan , Xiaowen Dong , Michael Bronstein

The group testing problem consists of determining a sparse subset of defective items from within a larger set of items via a series of tests, where each test outcome indicates whether at least one defective item is included in the test. We…

Information Theory · Computer Science 2026-04-24 Daniel McMorrow , Jonathan Scarlett

The objective of this work is to quantify the reconstruction error in sparse inverse problems with measures and stochastic noise, motivated by optimal sensor placement. To be useful in this context, the error quantities must be explicit in…

Numerical Analysis · Mathematics 2024-04-19 Phuoc-Truong Huynh , Konstantin Pieper , Daniel Walter

A symmetric subset of the reals is one that remains invariant under some reflection x --> c-x. Given 0 < x < 1, there exists a real number D(x) with the following property: if 0 < d < D(x), then every subset of [0,1] with measure x contains…

Number Theory · Mathematics 2007-05-23 Greg Martin , Kevin O'Bryant

The goal of ordinal embedding is to represent items as points in a low-dimensional Euclidean space given a set of constraints in the form of distance comparisons like "item $i$ is closer to item $j$ than item $k$". Ordinal constraints like…

Machine Learning · Statistics 2016-06-24 Lalit Jain , Kevin Jamieson , Robert Nowak

Designing computational experiments involving $\ell_1$ minimization with linear constraints in a finite-dimensional, real-valued space for receiving a sparse solution with a precise number $k$ of nonzero entries is, in general, difficult.…

Optimization and Control · Mathematics 2013-09-11 Christian Kruschel , Dirk A. Lorenz

Time-resolved CT is an advanced measurement technique that has been widely used to observe dynamic objects, including periodically varying structures such as hearts, lungs, or hearing structures. To reconstruct these objects from CT…

Medical Physics · Physics 2025-06-05 Qianwei Qu , Christian M. Schlepütz , Marco Stampanoni