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We study the minimum diameter problem for a set of inexact points. By inexact, we mean that the precise location of the points is not known. Instead, the location of each point is restricted to a contineus region ($\impre$ model) or a…

Computational Geometry · Computer Science 2017-04-03 Mohammad Ghodsi , Hamid Homapour , Masoud Seddighin

Consider a set $P$ of $n$ points in $\mathbb{R}^d$. In the discrete median line segment problem, the objective is to find a line segment bounded by a pair of points in $P$ such that the sum of the Euclidean distances from $P$ to the line…

Computational Geometry · Computer Science 2022-02-16 Ovidiu Daescu , Ka Yaw Teo

We study approximation algorithms for variants of the \emph{median string} problem, which asks for a string that minimizes the sum of edit distances from a given set of $m$ strings of length $n$. Only the straightforward $2$-approximation…

Data Structures and Algorithms · Computer Science 2020-11-03 Diptarka Chakraborty , Debarati Das , Robert Krauthgamer

In the $d$-Scattered Set problem we are asked to select at least $k$ vertices of a given graph, so that the distance between any pair is at least $d$. We study the problem's (in-)approximability and offer improvements and extensions of…

Computational Complexity · Computer Science 2019-10-15 Ioannis Katsikarelis , Michael Lampis , Vangelis Th. Paschos

The metric sketching problem is defined as follows. Given a metric on $n$ points, and $\epsilon>0$, we wish to produce a small size data structure (sketch) that, given any pair of point indices, recovers the distance between the points up…

Computational Geometry · Computer Science 2016-11-30 Piotr Indyk , Tal Wagner

We design a deterministic algorithm that, given $n$ points in a \emph{typical} constant degree regular~graph, queries $O(n)$ distances to output a constant factor approximation to the average distance among those points, thus answering a…

Data Structures and Algorithms · Computer Science 2025-10-22 Alexandros Eskenazis , Manor Mendel , Assaf Naor

We give a dimensionality reduction procedure to approximate the sum of distances of a given set of $n$ points in $R^d$ to any "shape" that lies in a $k$-dimensional subspace. Here, by "shape" we mean any set of points in $R^d$. Our…

Data Structures and Algorithms · Computer Science 2021-06-25 Zhili Feng , Praneeth Kacham , David P. Woodruff

In this article, we consider Poisson and Poisson convoluted geometric approximation to the sums of $n$ independent random variables under moment conditions. We use Stein's method to derive the approximation results in total variation…

Probability · Mathematics 2020-07-07 Pratima Eknath Kadu

We study the length of cycles of random permutations drawn from the Mallows distribution. Under this distribution, the probability of a permutation $\pi \in \mathbb{S}_n$ is proportional to $q^{\textrm{inv}(\pi)}$ where $0<q\le 1$ and…

Probability · Mathematics 2017-09-12 Alexey Gladkich , Ron Peled

For the constrained 2-means problem, we present a $O\left(dn+d({1\over\epsilon})^{O({1\over \epsilon})}\log n\right)$ time algorithm. It generates a collection $U$ of approximate center pairs $(c_1, c_2)$ such that one of pairs in $U$ can…

Computational Geometry · Computer Science 2018-08-14 Qilong Feng , Bin Fu

Let $D(n,r)$ be a random $r$-out regular directed multigraph on the set of vertices $\{1,\ldots,n\}$. In this work, we establish that for every $r \ge 2$, there exists $\eta_r>0$ such that $\text{diam}(D(n,r))=(1+\eta_r+o(1))\log_r{n}$. Our…

Probability · Mathematics 2015-04-28 Louigi Addario-Berry , Borja Balle , Guillem Perarnau

Let $p$ be an unknown and arbitrary probability distribution over $[0,1)$. We consider the problem of {\em density estimation}, in which a learning algorithm is given i.i.d. draws from $p$ and must (with high probability) output a…

Machine Learning · Computer Science 2014-11-04 Siu-On Chan , Ilias Diakonikolas , Rocco A. Servedio , Xiaorui Sun

For any finite point set in $D$-dimensional space equipped with the 1-norm, we present random linear embeddings to $k$-dimensional space, with a new metric, having the following properties. For any pair of points from the point set that are…

Probability · Mathematics 2020-11-09 Michael P. Casey

We study, in d-dimensions, the random walker with geometrically shrinking step sizes at each hop. We emphasize the integrated quantities such as expectation values, cumulants and moments rather than a direct study of the probability…

Statistical Mechanics · Physics 2009-11-11 Tonguc Rador

Consider a set $P$ of $n$ points picked uniformly and independently from $[0,1]^d$ for a constant dimension $d$ -- such a point set is extremely well behaved in many aspects. For example, for a fixed $r \in [0,1]$, we prove a new…

Computational Geometry · Computer Science 2023-11-01 Sariel Har-Peled , Elfarouk Harb

In the field of topological data analysis, persistence modules are used to express geometrical features of data sets. The matching distance $d_\mathcal{M}$ measures the difference between $2$-parameter persistence modules by taking the…

Algebraic Topology · Mathematics 2023-12-08 Håvard Bakke Bjerkevik , Michael Kerber

Let $T$ be a tree space (or tree network) represented by a weighted tree with $t$ vertices, and $S$ be a set of $n$ stochastic points in $T$, each of which has a fixed location with an independent existence probability. We investigate two…

Computational Geometry · Computer Science 2016-12-16 Jie Xue , Yuan Li

For a fixed integer $k\geqslant 2$, let $G\in \mathcal{G}(n,p)$ be a simple connected graph on $n\rightarrow\infty$ vertices with the expected degree $d=np$ satisfying $d\geqslant c$ and $d^{k-1}= o(n)$ for some large enough constant $c$.…

Combinatorics · Mathematics 2022-02-08 Fang Tian , Yun-Qin Sun , Zi-Long Liu

Let $G_n$ be a random geometric graph with vertex set $[n]$ based on $n$ i.i.d.\ random vectors $X_1,\ldots,X_n$ drawn from an unknown density $f$ on $\R^d$. An edge $(i,j)$ is present when $\|X_i -X_j\| \le r_n$, for a given threshold…

Machine Learning · Statistics 2023-11-23 Caelan Atamanchuk , Luc Devroye , Gabor Lugosi

Let $d_1\leq d_2\leq\ldots\leq d_{n\choose 2}$ denote the distances determined by $n$ points in the plane. It is shown that $\min\sum_i (d_{i+1}-d_i)^2=O(n^{-6/7})$, where the minimum is taken over all point sets with minimal distance $d_1…

Metric Geometry · Mathematics 2008-02-03 János Pach , Joel Spencer