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Related papers: Distance Reconstruction of Sparse Random Graphs

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We consider approximate distance oracles for edge-weighted n-vertex undirected planar graphs. Given fixed epsilon > 0, we present a (1+epsilon)-approximate distance oracle with O(n(loglog n)^2) space and O((loglog n)^3) query time. This…

Data Structures and Algorithms · Computer Science 2016-01-06 Christian Wulff-Nilsen

We investigate sublinear-time algorithms that take partially erased graphs represented by adjacency lists as input. Our algorithms make degree and neighbor queries to the input graph and work with a specified fraction of adversarial…

Data Structures and Algorithms · Computer Science 2020-12-01 Amit Levi , Ramesh Krishnan S. Pallavoor , Sofya Raskhodnikova , Nithin Varma

We study the efficient generation of random graphs with a prescribed expected degree sequence, focusing on rank-1 inhomogeneous models in which vertices are assigned weights and edges are drawn independently with probabilities proportional…

Data Structures and Algorithms · Computer Science 2026-04-24 Gianlorenzo D'Angelo , Riccardo Michielan

Network reconstruction consists in determining the unobserved pairwise couplings between $N$ nodes given only observational data on the resulting behavior that is conditioned on those couplings -- typically a time-series or independent…

Data Structures and Algorithms · Computer Science 2024-05-08 Tiago P. Peixoto

We consider problems of the following type: given a graph $G$, how many edges are needed in the worst case for a sparse subgraph $H$ that approximately preserves distances between a given set of node pairs $P$? Examples include pairwise…

Data Structures and Algorithms · Computer Science 2021-05-10 Greg Bodwin

We introduce a new graph-theoretic concept in the area of network monitoring. A set $M$ of vertices of a graph $G$ is a \emph{distance-edge-monitoring set} if for every edge $e$ of $G$, there is a vertex $x$ of $M$ and a vertex $y$ of $G$…

Data Structures and Algorithms · Computer Science 2022-09-26 Florent Foucaud , Shih-Shun Kao , Ralf Klasing , Mirka Miller , Joe Ryan

We study distributed algorithms for some fundamental problems in data summarization. Given a communication graph $G$ of $n$ nodes each of which may hold a value initially, we focus on computing $\sum_{i=1}^N g(f_i)$, where $f_i$ is the…

Data Structures and Algorithms · Computer Science 2019-08-07 Hsin-Hao Su , Hoa T. Vu

Given an undirected unweighted graph $G$ and a source set $S$ of $|S| = \sigma $ sources, we want to build a data structure which can process the following query {\sc Q}$(s,t,e):$ find the shortest distance from $s$ to $t$ avoiding an edge…

Data Structures and Algorithms · Computer Science 2018-05-02 Manoj Gupta , Aditi Singh

A $(1+\epsilon)$-approximate distance oracle of an edge-weighted graph is a data structure that returns an approximate shortest path distance between any two query vertices up to a $(1+\epsilon)$ factor. Thorup (FOCS 2001, JACM 2004) and…

Data Structures and Algorithms · Computer Science 2021-11-08 Hung Le , Christian Wulff-Nilsen

We present new and improved data structures that answer exact node-to-node distance queries in planar graphs. Such data structures are also known as distance oracles. For any directed planar graph on n nodes with non-negative lengths we…

Data Structures and Algorithms · Computer Science 2011-11-11 Shay Mozes , Christian Sommer

Graph spanners are sparse subgraphs that faithfully preserve the distances in the original graph up to small stretch. Spanner have been studied extensively as they have a wide range of applications ranging from distance oracles, labeling…

Data Structures and Algorithms · Computer Science 2018-05-16 Merav Parter , Eylon Yogev

We study the intersection of a random geometric graph with an Erd\H{o}s-R\'enyi graph. Specifically, we generate the random geometric graph $G(n, r)$ by choosing $n$ points uniformly at random from $D=[0, 1]^2$ and joining any two points…

Combinatorics · Mathematics 2024-11-08 Patrick Bennett , Alan Frieze , Wesley Pegden

Our main result is designing an algorithm that returns a vertex cover of $\mathcal{G}^\star$ with size at most $(3/2+\epsilon)$ times the expected size of the minimum vertex cover, using only $O(n/\epsilon p)$ non-adaptive queries. This…

Data Structures and Algorithms · Computer Science 2023-02-07 Mahsa Derakhshan , Naveen Durvasula , Nika Haghtalab

Let G be a simple, connected graph on n vertices. Let d_G(u,v) denote the distance between vertices u and v in G. A subgraph H of G is isometric if d_H(u,v)=d_G(u,v) for every u,v in V(H). We say that G is a distance-preserving graph if G…

Combinatorics · Mathematics 2014-05-08 Abdol-Hossein Esfahanian , Ronald Nussbaum , Dennis Ross , Bruce E. Sagan

In this paper, we address the problem of learning the structure of a pairwise graphical model from samples in a high-dimensional setting. Our first main result studies the sparsistency, or consistency in sparsity pattern recovery,…

Machine Learning · Computer Science 2012-02-28 Ali Jalali , Chris Johnson , Pradeep Ravikumar

We consider the problem of learning the nearest neighbor graph of a dataset of n items. The metric is unknown, but we can query an oracle to obtain a noisy estimate of the distance between any pair of items. This framework applies to…

Machine Learning · Statistics 2019-06-03 Blake Mason , Ardhendu Tripathy , Robert Nowak

Let $G$ be an $n$-vertex graph with $m$ edges. When asked a subset $S$ of vertices, a cut query on $G$ returns the number of edges of $G$ that have exactly one endpoint in $S$. We show that there is a bounded-error quantum algorithm that…

Data Structures and Algorithms · Computer Science 2020-08-05 Troy Lee , Miklos Santha , Shengyu Zhang

We study the Requirement Cut problem, a generalization of numerous classical graph partitioning problems including Multicut, Multiway Cut, $k$-Cut, and Steiner Multicut among others. Given a graph with edge costs, terminal groups $(S_1,…

Data Structures and Algorithms · Computer Science 2025-11-25 Nadym Mallek , Kirill Simonov

The Fr\'{e}chet distance is a well-studied similarity measure between curves that is widely used throughout computer science. Motivated by applications where curves stem from paths and walks on an underlying graph (such as a road network),…

Computational Geometry · Computer Science 2024-11-20 Anne Driemel , Ivor van der Hoog , Eva Rotenberg

Let $P$ be a set of $n$ points in the plane, where each point $p\in P$ has a transmission radius $r(p)>0$. The transmission graph defined by $P$ and the given radii, denoted by $\mathcal{G}_{\mathrm{tr}}(P)$, is the directed graph whose…

Computational Geometry · Computer Science 2022-10-13 Mark de Berg
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