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Suppose we are given a vector $f$ in $\R^N$. How many linear measurements do we need to make about $f$ to be able to recover $f$ to within precision $\epsilon$ in the Euclidean ($\ell_2$) metric? Or more exactly, suppose we are interested…

Classical Analysis and ODEs · Mathematics 2007-05-23 Emmanuel Candes , Terence Tao

Motivated by DNA-based storage applications, we study the problem of reconstructing a coded sequence from multiple traces. We consider the model where the traces are outputs of independent deletion channels, where each channel deletes each…

Information Theory · Computer Science 2022-07-13 Serge Kas Hanna

The problem of non-iterative one-shot and non-destructive correction of unavoidable mistakes arises in all Artificial Intelligence applications in the real world. Its solution requires robust separation of samples with errors from samples…

Machine Learning · Computer Science 2017-09-05 A. N. Gorban , I. Y. Tyukin

Recovery of the initial state of a high-dimensional system can require a large number of measurements. In this paper, we explain how this burden can be significantly reduced when randomized measurement operators are employed. Our work…

Systems and Control · Computer Science 2013-07-17 Borhan M. Sanandaji , Michael B. Wakin , Tyrone L. Vincent

We study Linial-Meshulam random 2-complexes, which are two-dimensional analogues of Erd\H{o}s-R\'enyi random graphs. We find the threshold for simple connectivity to be p = n^{-1/2}. This is in contrast to the threshold for vanishing of the…

Group Theory · Mathematics 2011-05-11 Eric Babson , Christopher Hoffman , Matthew Kahle

Suppose a graph $G$ is stochastically created by uniformly sampling vertices along a line segment and connecting each pair of vertices with a probability that is a known decreasing function of their distance. We ask if it is possible to…

Data Structures and Algorithms · Computer Science 2020-06-09 Yu Chen , Sampath Kannan , Sanjeev Khanna

It is shown that given a set of $N$ points in the plane or on the sphere, there is a subset of size $\gtrsim N^{1/3}/\log N$ with all pairwise distances between points distinct.

Combinatorics · Mathematics 2014-04-08 Marcos Charalambides

Embedding graphs in a geographical or latent space, i.e.\ inferring locations for vertices in Euclidean space or on a smooth manifold or submanifold, is a common task in network analysis, statistical inference, and graph visualization. We…

Computational Geometry · Computer Science 2022-05-18 Varsha Dani , Josep Díaz , Thomas P. Hayes , Cristopher Moore

We establish a bound of $O(n^2k^{1+\eps})$, for any $\eps>0$, on the combinatorial complexity of the set $\T$ of line transversals of a collection $\P$ of $k$ convex polyhedra in $\reals^3$ with a total of $n$ facets, and present a…

Computational Geometry · Computer Science 2008-07-09 Haim Kaplan , Natan Rubin , Micha Sharir

We study the problem of recovering a structured signal from independently and identically drawn linear measurements. A convex penalty function $f(\cdot)$ is considered which penalizes deviations from the desired structure, and signal…

Statistics Theory · Mathematics 2019-06-21 Ehsan Abbasi , Fariborz Salehi , Babak Hassibi

The trace reconstruction problem studies the number of noisy samples needed to recover an unknown string $\boldsymbol{x}\in\{0,1\}^n$ with high probability, where the samples are independently obtained by passing $\boldsymbol{x}$ through a…

Information Theory · Computer Science 2021-04-15 Jin Sima , Jehoshua Bruck

We derive various sharp bounds on moments of the distance between two independent random vectors taking values in a Banach space.

Functional Analysis · Mathematics 2019-05-06 Assaf Naor , Krzysztof Oleszkiewicz

We study the problem of recovering a collection of $n$ numbers from the evaluation of $m$ power sums. This yields a system of polynomial equations, which can be underconstrained ($m < n$), square ($m = n$), or overconstrained ($m > n$).…

Algebraic Geometry · Mathematics 2021-06-29 Hana Melánová , Bernd Sturmfels , Rosa Winter

Distance correlation is a novel class of multivariate dependence measure, taking positive values between 0 and 1, and applicable to random vectors of arbitrary dimensions, not necessarily equal. It offers several advantages over the…

Computation · Statistics 2024-05-06 Blanca E. Monroy-Castillo , M. A , Jácome , Ricardo Cao

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

In 1960, R\'enyi asked for the number of random queries necessary to recover a hidden bijective labeling of n distinct objects. In each query one selects a random subset of labels and asks, what is the set of objects that have these labels?…

Probability · Mathematics 2016-05-09 Michael Drmota , Abram Magner , Wojciech Szpankowski

An important result in discrepancy due to Banaszczyk states that for any set of $n$ vectors in $\mathbb{R}^m$ of $\ell_2$ norm at most $1$ and any convex body $K$ in $\mathbb{R}^m$ of Gaussian measure at least half, there exists a $\pm 1$…

Data Structures and Algorithms · Computer Science 2017-08-04 Nikhil Bansal , Daniel Dadush , Shashwat Garg , Shachar Lovett

We consider a sequence of identically independently distributed random samples from an absolutely continuous probability measure in one dimension with unbounded density. We establish a new rate of convergence of the $\infty-$Wasserstein…

Probability · Mathematics 2018-08-03 Anning Liu , Jian-Guo Liu , Yulong Lu

This short note modifies a reconstruction method by the author (Comm. PDE, 45(9):1118-1133, 2020), for reconstructing piecewise constant conductivities in the Calder\'on problem (electrical impedance tomography). In the former paper, a…

Analysis of PDEs · Mathematics 2025-12-08 Henrik Garde

We consider the problem of choosing Euclidean points to maximize the sum of their weighted pairwise distances, when each point is constrained to a ball centered at the origin. We derive a dual minimization problem and show strong duality…

Data Structures and Algorithms · Computer Science 2010-07-02 Neal E. Young
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