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Related papers: Stochastic approximation of lamplighter metrics

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We introduce and study the notion of an outer bi-Lipschitz extension of a map between Euclidean spaces. The notion is a natural analogue of the notion of a Lipschitz extension of a Lipschitz map. We show that for every map $f$ there exists…

Data Structures and Algorithms · Computer Science 2018-11-09 Sepideh Mahabadi , Konstantin Makarychev , Yury Makarychev , Ilya Razenshteyn

The main question studied in this article may be viewed as a nonlinear analogue of Dvoretzky's theorem in Banach space theory or as part of Ramsey theory in combinatorics. Given a finite metric space on n points, we seek its subspace of…

Metric Geometry · Mathematics 2012-11-15 Yair Bartal , Nathan Linial , Manor Mendel , Assaf Naor

We initiate the study of metric embeddings with \emph{outliers}. Given some metric space $(X,\rho)$ we wish to find a small set of outlier points $K \subset X$ and either an isometric or a low-distortion embedding of $(X\setminus K,\rho)$…

Data Structures and Algorithms · Computer Science 2015-08-17 Anastasios Sidiropoulos , Yusu Wang

Given an arbitrary set of high dimensional points in $\ell_1$, there are known negative results that preclude the possibility of always mapping them to a low dimensional $\ell_1$ space while preserving distances with small multiplicative…

Data Structures and Algorithms · Computer Science 2024-04-09 Moses Charikar , Spencer Compton , Chirag Pabbaraju

In this paper we study {\em terminal embeddings}, in which one is given a finite metric $(X,d_X)$ (or a graph $G=(V,E)$) and a subset $K \subseteq X$ of its points are designated as {\em terminals}. The objective is to embed the metric into…

Data Structures and Algorithms · Computer Science 2016-03-09 Michael Elkin , Arnold Filtser , Ofer Neiman

We prove that the lamplighter group admits an injective Lipschitz map to any finitely generated metabelian group which is not virtually nilpotent. This implies that finitely generated metabelian groups satisfy the ``analytically…

Group Theory · Mathematics 2024-01-17 Antoine Gournay , Corentin Le Coz

Low-dimensional embeddings are essential for machine learning tasks involving graphs, such as node classification, link prediction, community detection, network visualization, and network compression. Although recent studies have identified…

Machine Learning · Computer Science 2025-03-04 Nikolaos Nakis , Niels Raunkjær Holm , Andreas Lyhne Fiehn , Morten Mørup

A distortion lower bound of $\Omega(\log(h)^{1/p})$ is proven for embedding the complete countably branching hyperbolic tree of height $h$ into a Banach space admitting an equivalent norm satisfying property $(\beta)$ of Rolewicz with…

Metric Geometry · Mathematics 2017-09-27 Florent P. Baudier , Sheng Zhang

We study deterministic online embeddings of metrics spaces into normed spaces and into trees against an adaptive adversary. Main results include a polynomial lower bound on the (multiplicative) distortion of embedding into Euclidean spaces,…

Computational Geometry · Computer Science 2023-03-29 Ilan Newman , Yuri Rabinovich

Two definitions for the rectfiability of hypersurfaces in Heisenberg groups $\mathbb{H}^n$ have been proposed: one based on $\mathbb{H}$-regular surfaces, and the other on Lipschitz images of subsets of codimension-$1$ vertical subgroups.…

Classical Analysis and ODEs · Mathematics 2021-07-09 Daniela Di Donato , Katrin Fässler , Tuomas Orponen

We consider the problem of computing the smallest possible distortion for embedding of a given n-point metric space into R^d, where d is fixed (and small). For d=1, it was known that approximating the minimum distortion with a factor better…

Computational Geometry · Computer Science 2009-09-29 Jiri Matousek , Anastasios Sidiropoulos

Let X and Y be two infinite-dimensional Banach spaces. If X is crudely finitely representable in every finite-codimensional subspace of Y, then any proper subset of X almost bi-Lipschitz embeds into Y, in a sense quite close to that of F.…

Functional Analysis · Mathematics 2023-10-09 François Netillard

Using lattice approximations of Euclidean space, we develop a way to approximate stable processes that are represented by stochastic integrals over Euclidean space. Via a stable version of the Lindeberg-Feller Theorem we show that the…

Probability · Mathematics 2013-02-19 Clément Dombry , Paul Jung

We focus our attention on the notion of intrinsic Lipschitz graphs, inside a special class of metric spaces i.e. the Carnot groups. More precisely, we provide a characterization of locally intrinsic Lipschitz functions in Carnot groups of…

Differential Geometry · Mathematics 2019-03-08 Daniela Di Donato

The end compactification |\Gamma| of the locally finite graph \Gamma is the union of the graph and its ends, endowed with a suitable topology. We show that \pi_1(|\Gamma|) embeds into a nonstandard free group with hyperfinitely many…

Geometric Topology · Mathematics 2012-03-30 Isaac Goldbring , Alessandro Sisto

We present a novel graph embedding space (i.e., a set of measures on graphs) for performing statistical analyses of networks. Key improvements over existing approaches include discovery of "motif-hubs" (multiple overlapping significant…

Disordered Systems and Neural Networks · Physics 2007-05-23 Etay Ziv , Robin Koytcheff , Manuel Middendorf , Chris Wiggins

We study finite element approximations of second-order elliptic problems with measure-valued right-hand sides supported on lower-dimensional sets. The exact solution generally lacks $H^1$-regularity due to the source singularity, which…

Numerical Analysis · Mathematics 2026-03-10 Huadong Gao , Yuhui Huang

Let $T$ be a compact, metrisable and strongly countable-dimensional topological space. Let $\mathcal{M}^T$ be the set of all metrics $d$ on $T$ compatible with its topology, and equip $\mathcal{M}^T$ with the topology of uniform…

Functional Analysis · Mathematics 2024-05-31 Filip Talimdjioski

Establishing Lipschitz stability estimates is crucial for ensuring the mathematical robustness of neural network (NN) approximations in machine learning (ML)-based parameter estimation, particularly in physics-informed settings. In this…

Numerical Analysis · Mathematics 2025-11-25 Mahadevan Ganesh , Stuart C. Hawkins , Darko Volkov

We prove that if a simply connected nilpotent Lie group quasi-isometrically embeds into an $L^1$ space, then it is abelian. We reach this conclusion by proving that every Carnot group that biLipschitz embeds into $L^1$ is abelian. Our proof…

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