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The adjacency matrix is the most fundamental and intuitive object in graph analysis that is useful not only mathematically but also for visualizing the structures of graphs. Because the appearance of an adjacency matrix is critically…

Social and Information Networks · Computer Science 2023-04-07 Tatsuro Kawamoto , Teruyoshi Kobayashi

One of the simplest problems on directed graphs is that of identifying the set of vertices reachable from a designated source vertex. This problem can be solved easily sequentially by performing a graph search, but efficient parallel…

Data Structures and Algorithms · Computer Science 2017-11-07 Jeremy T. Fineman

Consider the family of bounded degree graphs in any minor-closed family (such as planar graphs). Let d be the degree bound and n be the number of vertices of such a graph. Graphs in these classes have hyperfinite decompositions, where, for…

Data Structures and Algorithms · Computer Science 2021-05-04 Akash Kumar , C. Seshadhri , Andrew Stolman

A graph whose edges only appear at certain points in time is called a temporal graph (among other names). Such a graph is temporally connected if each ordered pair of vertices is connected by a path which traverses edges in chronological…

Discrete Mathematics · Computer Science 2023-12-19 Arnaud Casteigts , Michael Raskin , Malte Renken , Viktor Zamaraev

An adjacency labeling scheme is a method that assigns labels to the vertices of a graph such that adjacency between vertices can be inferred directly from the assigned label, without using a centralized data structure. We devise adjacency…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-02-16 Casper Petersen , Noy Rotbart , Jakob Grue Simonsen , Christian Wulff-Nilsen

The problem of finding the degeneracy of a graph is a subproblem of the k-core decomposition problem. In this paper, we present a (1 + epsilon)-approximate solution to the degeneracy problem which runs in O(n log n) time, sublinear in the…

Data Structures and Algorithms · Computer Science 2022-11-16 Valerie King , Alex Thomo , Quinton Yong

We introduce a new approach to spectral sparsification that approximates the quadratic form of the pseudoinverse of a graph Laplacian restricted to a subspace. We show that sparsifiers with a near-linear number of edges in the dimension of…

Data Structures and Algorithms · Computer Science 2018-10-09 Huan Li , Aaron Schild

We introduce the following submodular generalization of the Shortest Cycle problem. For a nonnegative monotone submodular cost function $f$ defined on the edges (or the vertices) of an undirected graph $G$, we seek for a cycle $C$ in $G$ of…

Data Structures and Algorithms · Computer Science 2022-11-10 Fedor V. Fomin , Petr A. Golovach , Tuukka Korhonen , Daniel Lokshtanov , Giannos Stamoulis

Consider an undirected graph $G = (VG, EG)$ and a set of six \emph{terminals} $T = \set{s_1, s_2, s_3, t_1, t_2, t_3} \subseteq VG$. The goal is to find a collection $\calP$ of three edge-disjoint paths $P_1$, $P_2$, and $P_3$, where $P_i$…

Combinatorics · Mathematics 2010-03-17 Maxim Babenko , Ignat Kolesnichenko , Ilya Razenshteyn

We consider the fundamental problems of approximately counting the numbers of edges and triangles in a graph in sublinear time. Previous algorithms for these tasks are significantly more efficient under a promise that the arboricity of the…

Data Structures and Algorithms · Computer Science 2025-09-25 Talya Eden , Ronitt Rubinfeld , Arsen Vasilyan

In the Distance Oracle problem, the goal is to preprocess $n$ vectors $x_1, x_2, \cdots, x_n$ in a $d$-dimensional metric space $(\mathbb{X}^d, \| \cdot \|_l)$ into a cheap data structure, so that given a query vector $q \in \mathbb{X}^d$…

Data Structures and Algorithms · Computer Science 2022-05-31 Yichuan Deng , Zhao Song , Omri Weinstein , Ruizhe Zhang

We revisit once more the problem of designing an oracle for answering connectivity queries in undirected graphs in the presence of vertex failures. Specifically, given an undirected graph $G$ with $n$ vertices and $m$ edges and an integer…

Data Structures and Algorithms · Computer Science 2023-09-06 Evangelos Kosinas

We show how to construct an overlay network of constant degree and diameter $O(\log n)$ in time $O(\log n)$ starting from an arbitrary weakly connected graph. We assume a synchronous communication network in which nodes can send messages to…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-07-28 Thorsten Götte , Kristian Hinnenthal , Christian Scheideler , Julian Werthmann

We study recovering a 1D order from a noisy, locally sampled pairwise comparison matrix under a tight query budget. We recast the task as reconstructing a sparse, noisy line graph and present, to our knowledge, the first method that…

Data Structures and Algorithms · Computer Science 2025-11-13 Fuming Yang , Yaron Meirovitch , Jeff W. Lichtman

We present a new sublinear time algorithm for approximating the spectral density (eigenvalue distribution) of an $n\times n$ normalized graph adjacency or Laplacian matrix. The algorithm recovers the spectrum up to $\epsilon$ accuracy in…

Data Structures and Algorithms · Computer Science 2022-04-18 Vladimir Braverman , Aditya Krishnan , Christopher Musco

We study sublinear time algorithms for estimating the size of maximum matching. After a long line of research, the problem was finally settled by Behnezhad [FOCS'22], in the regime where one is willing to pay an approximation factor of $2$.…

Data Structures and Algorithms · Computer Science 2023-04-28 Sayan Bhattacharya , Peter Kiss , Thatchaphol Saranurak

Given a conjunctive query and a database instance, we aim to develop an index that can efficiently answer spatial queries on the results of a conjunctive query. We are interested in some commonly used spatial queries, such as range…

Databases · Computer Science 2025-09-15 Aryan Esmailpour , Xiao Hu , Stavros Sintos

Most of the literature on spanners focuses on building the graph from scratch. This paper instead focuses on adding edges to improve an existing graph. A major open problem in this field is: given a graph embedded in a metric space, and a…

Computational Geometry · Computer Science 2022-12-20 Joachim Gudmundsson , Sampson Wong

Outstanding achievements of graph neural networks for spatiotemporal time series analysis show that relational constraints introduce an effective inductive bias into neural forecasting architectures. Often, however, the relational…

Machine Learning · Computer Science 2023-08-03 Andrea Cini , Daniele Zambon , Cesare Alippi

Geometric data structures have been extensively studied in the regime where the dimension is much smaller than the number of input points. But in many scenarios in Machine Learning, the dimension can be much higher than the number of points…

Data Structures and Algorithms · Computer Science 2025-04-07 Martin G. Herold , Danupon Nanongkai , Joachim Spoerhase , Nithin Varma , Zihang Wu
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