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We resolve a conjecture of Rob Morris concerning bijections on the hypercube. Specifically, we show that for any bijection $f : \{-1,1\}^n \to \{-1,1\}^n$, \[ \Pr_{x,y \in \{-1,1\}^n}\big[ \langle x,y \rangle \ge 0 \;\text{and}\; \langle…

Combinatorics · Mathematics 2026-04-21 Ijay Narang , Muchen Ju

We consider the problem of embedding a subset of $\mathbb{R}^n$ into a low-dimensional Hamming cube in an almost isometric way. We construct a simple, data-oblivious, and computationally efficient map that achieves this task with high…

Probability · Mathematics 2022-09-07 Sjoerd Dirksen , Shahar Mendelson , Alexander Stollenwerk

Let $\mathcal{M}$ be a smooth submanifold of $\mathbb{R}^n$ equipped with the Euclidean (chordal) metric. This note considers the smallest dimension $m$ for which there exists a bi-Lipschitz function $f: \mathcal{M} \mapsto \mathbb{R}^m$…

Numerical Analysis · Mathematics 2021-05-31 Mark Iwen , Arman Tavakoli , Benjamin Schmidt

Spurred by the influential work of Viola (Journal of Computing 2012), the past decade has witnessed an active line of research into the complexity of (approximately) sampling distributions, in contrast to the traditional focus on the…

Computational Complexity · Computer Science 2024-02-28 Daniel M. Kane , Anthony Ostuni , Kewen Wu

A metric probability space $(\Omega,d)$ obeys the ${\it concentration\; of\; measure\; phenomenon}$ if subsets of measure $1/2$ enlarge to subsets of measure close to 1 as a transition parameter $\epsilon$ approaches a limit. In this paper…

Probability · Mathematics 2024-08-07 Jonathan Root , Mark Kon

For $n\in \mathbb{N}$ consider the $n$-dimensional hypercube as equal to the vector space $\mathbb{F}_2^n$, where $\mathbb{F}_2$ is the field of size two. Endow $\mathbb{F}_2^n$ with the Hamming metric, i.e., with the metric induced by the…

Functional Analysis · Mathematics 2015-01-28 Assaf Naor , Gideon Schechtman

We derive bounds for the ball $L_p$-discrepancies in the Hamming space for $0<p<\infty$ and $p=\infty$. Sharp estimates of discrepancies have been obtained for many spaces such as the Euclidean spheres and more general compact Riemannian…

Metric Geometry · Mathematics 2020-08-31 Alexander Barg , Maxim Skriganov

The hypothesis that high dimensional data tend to lie in the vicinity of a low dimensional manifold is the basis of manifold learning. The goal of this paper is to develop an algorithm (with accompanying complexity guarantees) for fitting a…

Statistics Theory · Mathematics 2013-12-23 Charles Fefferman , Sanjoy Mitter , Hariharan Narayanan

A natural measure of smoothness of a Boolean function is its sensitivity (the largest number of Hamming neighbors of a point which differ from it in function value). The structure of smooth or equivalently low-sensitivity functions is still…

Computational Complexity · Computer Science 2015-08-12 Parikshit Gopalan , Noam Nisan , Rocco A. Servedio , Kunal Talwar , Avi Wigderson

The logarithmic Sobolev inequality for the Hamming cube {0,1}^n states that for any real-valued function f on the cube holds E(f,f) \ge 2 Ent(f^2), where E(f,f) is the appropriate Dirichlet form (also known as "sum of influences"). We show…

Combinatorics · Mathematics 2008-07-11 Alex Samorodnitsky

Binary embedding is the problem of mapping points from a high-dimensional space to a Hamming cube in lower dimension while preserving pairwise distances. An efficient way to accomplish this is to make use of fast embedding techniques…

Data Structures and Algorithms · Computer Science 2016-03-15 Samet Oymak

We study here limit spaces $(M_\alpha,g_\alpha,p_\alpha)\stackrel{GH}{\rightarrow} (Y,d_Y,p)$, where the $M_\alpha$ have a lower Ricci curvature bound and are volume noncollapsed. Such limits $Y$ may be quite singular, however it is known…

Differential Geometry · Mathematics 2011-11-10 Tobias Holck Colding , Aaron Naber

A probability distribution over the Boolean cube is monotone if flipping the value of a coordinate from zero to one can only increase the probability of an element. Given samples of an unknown monotone distribution over the Boolean cube, we…

Data Structures and Algorithms · Computer Science 2020-02-11 Ronitt Rubinfeld , Arsen Vasilyan

Let $M$ be a separable metric space. We say that $f=(f_n):M\to c_0$ is a good-$\lambda$-embedding if, whenever $x,y\in M$, $x\ne y$ implies $d(x,y)\le\Vert f(x)-f(y)\Vert$ and, for each $n$, $Lip(f_n)<\lambda$, where $Lip(f_n)$ denotes the…

Functional Analysis · Mathematics 2016-12-08 Florent P. Baudier , Robert Deville

Let $F^n$ be the binary $n$-cube, or binary Hamming space of dimension $n$, endowed with the Hamming distance, and ${\cal E}^n$ (respectively, ${\cal O}^n$) the set of vectors with even (respectively, odd) weight. For $r\geq 1$ and $x\in…

Discrete Mathematics · Computer Science 2007-05-23 Charon Cohen , Hudry Lobstein

We characterize uniformly perfect, complete, doubling metric spaces which embed bi- Lipschitzly into Euclidean space. Our result applies in particular to spaces of Grushin type equipped with Carnot-Carath\'eodory distance. Hence we obtain…

Metric Geometry · Mathematics 2011-05-13 Jeehyeon Seo

Binary embedding is a nonlinear dimension reduction methodology where high dimensional data are embedded into the Hamming cube while preserving the structure of the original space. Specifically, for an arbitrary $N$ distinct points in…

Data Structures and Algorithms · Computer Science 2019-01-24 Xinyang Yi , Constantine Caramanis , Eric Price

It is known that if $M$ is a finite-dimensional Banach space, or a strictly convex space, or the space $\ell_1$, then every non-expansive bijection $F: B_M \to B_M$ is an isometry. We extend these results to non-expansive bijections $F: B_E…

Functional Analysis · Mathematics 2018-07-16 Olesia Zavarzina

We prove a vertex isoperimetric inequality for the $n$-dimensional Hamming ball $\mathcal{B}_n(R)$ of radius $R$. The isoperimetric inequality is sharp up to a constant factor for sets that are comparable to $\mathcal{B}_n(R)$ in size. A…

Combinatorics · Mathematics 2022-02-10 Zilin Jiang , Amir Yehudayoff

This article investigates the probabilistic relationship between quantum classification of Boolean functions and their Hamming distance. By integrating concepts from quantum computing, information theory, and combinatorics, we explore how…

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