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We consider approximation algorithms for covering integer programs of the form min $\langle c, x \rangle $ over $x \in \mathbb{N}^n $ subject to $A x \geq b $ and $x \leq d$; where $A \in \mathbb{R}_{\geq 0}^{m \times n}$, $b \in…

Data Structures and Algorithms · Computer Science 2018-11-20 Chandra Chekuri , Kent Quanrud

In this paper, we study the linear separability problem for stochastic geometric objects under the well-known unipoint/multipoint uncertainty models. Let $S=S_R \cup S_B$ be a given set of stochastic bichromatic points, and define $n =…

Computational Geometry · Computer Science 2016-04-06 Jie Xue , Yuan Li , Ravi Janardan

Center-based clustering is a fundamental primitive for data analysis and becomes very challenging for large datasets. In this paper, we focus on the popular $k$-median and $k$-means variants which, given a set $P$ of points from a metric…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-10-01 Alessio Mazzetto , Andrea Pietracaprina , Geppino Pucci

In this paper, we study the $r$-gather problem, a natural formulation of minimum-size clustering in metric spaces. The goal of $r$-gather is to partition $n$ points into clusters such that each cluster has size at least $r$, and the maximum…

Data Structures and Algorithms · Computer Science 2021-06-08 Alessandro Epasto , Mohammad Mahdian , Vahab Mirrokni , Peilin Zhong

We discuss the optimal matching solution for both the assignment problem and the matching problem in one dimension for a large class of convex cost functions. We consider the problem in a compact set with the topology both of the interval…

Disordered Systems and Neural Networks · Physics 2017-10-11 Sergio Caracciolo , Matteo D'Achille , Gabriele Sicuro

The (unweighted) point-separation problem asks, given a pair of points $s$ and $t$ in the plane, and a set of candidate geometric objects, for the minimum-size subset of objects whose union blocks all paths from $s$ to $t$. Recent work has…

Computational Geometry · Computer Science 2026-02-16 Jayson Lynch , Jack Spalding-Jamieson

This paper introduces the \emph{$d$-distance $b$-matching problem}, in which we are given a bipartite graph $G=(S,T;E)$ with $S=\{s_1,\dots,s_n\}$, a weight function on the edges, an integer $d\in\mathbb{Z}_+$ and a degree bound function…

Discrete Mathematics · Computer Science 2023-11-29 Péter Madarasi

A subset of points in a metric space is said to resolve it if each point in the space is uniquely characterized by its distance to each point in the subset. In particular, resolving sets can be used to represent points in abstract metric…

Discrete Mathematics · Computer Science 2024-06-28 Manuel E. Lladser , Alexander J. Paradise

In the online metric matching problem, $n$ servers and $n$ requests lie in a metric space. Servers are available upfront, and requests arrive sequentially. An arriving request must be matched immediately and irrevocably to an available…

Data Structures and Algorithms · Computer Science 2026-04-22 Yingxi Li , Ellen Vitercik , Mingwei Yang

In this paper, we consider the problem of choosing disks (that we can think of as corresponding to wireless sensors) so that given a set of input points in the plane, there exists no path between any pair of these points that is not…

Computational Geometry · Computer Science 2011-05-20 Matt Gibson , Gaurav Kanade , Kasturi Varadarajan

An $\epsilon$-approximate incidence between a point and some geometric object (line, circle, plane, sphere) occurs when the point and the object lie at distance at most $\epsilon$ from each other. Given a set of points and a set of objects,…

Computational Geometry · Computer Science 2020-05-19 Dror Aiger , Haim Kaplan , Micha Sharir

Metric search is concerned with the efficient evaluation of queries in metric spaces. In general,a large space of objects is arranged in such a way that, when a further object is presented as a query, those objects most similar to the query…

Information Retrieval · Computer Science 2017-10-24 Richard Connor , Lucia Vadicamo , Franco Alberto Cardillo , Fausto Rabitti

Distance metric learning has attracted a lot of interest for solving machine learning and pattern recognition problems over the last decades. In this work we present a simple approach based on concepts from statistical physics to learn…

Machine Learning · Computer Science 2021-06-11 Dusan Stosic , Darko Stosic , Teresa B. Ludermir , Borko Stosic

Metric embeddings are a widely used method in algorithm design, where generally a ``complex'' metric is embedded into a simpler, lower-dimensional one. Historically, the theoretical computer science community has focused on bi-Lipschitz…

Data Structures and Algorithms · Computer Science 2025-05-19 Ainesh Bakshi , Vincent Cohen-Addad , Samuel B. Hopkins , Rajesh Jayaram , Silvio Lattanzi

Packing problems are an important class of optimization problems. The probably most well-known problem if this type is knapsack and many generalizations of it have been studied in the literature like Two-dimensional Geometric Knapsack…

Data Structures and Algorithms · Computer Science 2019-11-26 Tobias Mömke , Andreas Wiese

$\newcommand{\Re}{\mathbb{R}}$We study the minWSPD problem of computing the minimum-size well-separated pairs decomposition of a set of points, and show constant approximation algorithms in low-dimensional Euclidean space and doubling…

Computational Geometry · Computer Science 2026-02-04 Kevin Buchin , Jacobus Conradi , Sariel Har-Peled , Antonia Kalb , Abhiruk Lahiri , Lukas Plätz , Carolin Rehs , Sampson Wong

Given a graph $G$, the sparsest-cut problem asks to find the set of vertices $S$ which has the least expansion defined as $$\phi_G(S) := \frac{w(E(S,\bar{S}))}{\min \set{w(S), w(\bar{S})}}, $$ where $w$ is the total edge weight of a subset.…

Data Structures and Algorithms · Computer Science 2013-10-09 Anand Louis , Konstantin Makarychev

We study the classical scheduling problem on parallel machines %with precedence constraints where the precedence graph has the bounded depth $h$. Our goal is to minimize the maximum completion time. We focus on developing approximation…

Data Structures and Algorithms · Computer Science 2023-02-02 Bin Fu , Yumei Huo , Hairong Zhao

The Gromov-Wasserstein distances were proposed a few years ago to compare distributions which do not lie in the same space. In particular, they offer an interesting alternative to the Wasserstein distances for comparing probability measures…

Probability · Mathematics 2021-04-19 Antoine Salmona , Julie Delon , Agnès Desolneux

In this article, we consider the following capacitated covering problem. We are given a set $P$ of $n$ points and a set $\mathcal{B}$ of balls from some metric space, and a positive integer $U$ that represents the capacity of each of the…

Data Structures and Algorithms · Computer Science 2017-12-13 Sayan Bandyapadhyay , Santanu Bhowmick , Tanmay Inamdar , Kasturi Varadarajan