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We investigate local computation algorithms (LCA) for two-coloring of $k$-uniform hypergraphs. We focus on hypergraph instances that satisfy strengthened assumption of the Lov\'{a}sz Local Lemma of the form $2^{1-\alpha k} (\Delta+1)…

Data Structures and Algorithms · Computer Science 2023-05-05 Andrzej Dorobisz , Jakub Kozik

We design and engineer Fast-Sparse-Spanner, a simple and practical (fast and memory-efficient) algorithm for constructing sparse low stretch-factor geometric graphs on large pointsets in the plane. To our knowledge, this is the first…

Computational Geometry · Computer Science 2023-05-22 FNU Shariful , Justin Weathers , Anirban Ghosh , Giri Narasimhan

Given a source of iid samples of edges of an input graph $G$ with $n$ vertices and $m$ edges, how many samples does one need to compute a constant factor approximation to the maximum matching size in $G$? Moreover, is it possible to obtain…

Data Structures and Algorithms · Computer Science 2019-07-15 Michael Kapralov , Slobodan Mitrović , Ashkan Norouzi-Fard , Jakab Tardos

In this work, we present the first local-decoding algorithm for expander codes. This yields a new family of constant-rate codes that can recover from a constant fraction of errors in the codeword symbols, and where any symbol of the…

Information Theory · Computer Science 2015-01-08 Brett Hemenway , Rafail Ostrovsky , Mary Wootters

In this work, we give a unifying view of locality in four settings: distributed algorithms, sequential greedy algorithms, dynamic algorithms, and online algorithms. We introduce a new model of computing, called the online-LOCAL model: the…

Data Structures and Algorithms · Computer Science 2022-11-15 Amirreza Akbari , Navid Eslami , Henrik Lievonen , Darya Melnyk , Joona Särkijärvi , Jukka Suomela

This paper presents a unified analysis framework that captures recent advances in the study of local-optimality characterizations for codes on graphs. These local-optimality characterizations are based on combinatorial structures embedded…

Information Theory · Computer Science 2012-08-15 Guy Even , Nissim Halabi

Graph spanners are sparse subgraphs which approximately preserve all pairwise shortest-path distances in an input graph. The notion of approximation can be additive, multiplicative, or both, and many variants of this problem have been…

Data Structures and Algorithms · Computer Science 2019-11-19 Manuel Fernandez , David P. Woodruff , Taisuke Yasuda

An $(\alpha,\beta)$-spanner of a weighted graph $G=(V,E)$, is a subgraph $H$ such that for every $u,v\in V$, $d_G(u,v) \le d_H(u,v)\le\alpha\cdot d_G(u,v)+\beta$. The main parameters of interest for spanners are their size (number of edges)…

Data Structures and Algorithms · Computer Science 2024-11-01 Yuval Gitlitz , Ofer Neiman , Richard Spence

We consider the task of designing Local Computation Algorithms (LCA) for applications of the Lov\'{a}sz Local Lemma (LLL). LCA is a class of sublinear algorithms proposed by Rubinfeld et al.~\cite{Ronitt} that have received a lot of…

Data Structures and Algorithms · Computer Science 2020-07-08 Dimitris Achlioptas , Themis Gouleakis , Fotis Iliopoulos

Given a point set $P$ in the Euclidean plane and a parameter $t$, we define an \emph{oriented $t$-spanner} $G$ as an oriented subgraph of the complete bi-directed graph such that for every pair of points, the shortest closed walk in $G$…

Computational Geometry · Computer Science 2025-11-13 Kevin Buchin , Joachim Gudmundsson , Antonia Kalb , Aleksandr Popov , Carolin Rehs , André van Renssen , Sampson Wong

We describe approximation algorithms in Linial's classic LOCAL model of distributed computing to find maximum-weight matchings in a hypergraph of rank $r$. Our main result is a deterministic algorithm to generate a matching which is an…

Data Structures and Algorithms · Computer Science 2023-10-13 David G. Harris

We present a non-algebraic, locality-preserving framework for triangle detection in worst-case sparse graphs. Our algorithm processes the graph in $O(\log n)$ independent layers and partitions incident edges into prefix-based classes where…

Data Structures and Algorithms · Computer Science 2025-09-04 Hongyi Duan , Jian'an Zhang

In a seminal STOC'95 paper, titled "Euclidean spanners: short, thin and lanky", Arya et al. devised a construction of Euclidean $(1+\eps)$-spanners that achieves constant degree, diameter $O(\log n)$, and weight $O(\log^2 n) \cdot…

Data Structures and Algorithms · Computer Science 2012-11-28 Michael Elkin , Shay Solomon

As an important coding scheme in modern distributed storage systems, locally repairable codes (LRCs) have attracted a lot of attentions from perspectives of both practical applications and theoretical research. As a major topic in the…

Information Theory · Computer Science 2021-01-01 Xiangliang Kong , Xin Wang , Gennnian Ge

It was recently shown that a version of the greedy algorithm gives a construction of fault-tolerant spanners that is size-optimal, at least for vertex faults. However, the algorithm to construct this spanner is not polynomial-time, and the…

Data Structures and Algorithms · Computer Science 2020-05-26 Michael Dinitz , Caleb Robelle

Effective Resistance (ER) is a fundamental tool in various graph learning tasks. In this paper, we address the problem of efficiently approximating ER on a graph $\mathcal{G}=(\mathcal{V},\mathcal{E})$ with $n$ vertices and $m$ edges.…

Data Structures and Algorithms · Computer Science 2025-07-08 Yichun Yang , Rong-Hua Li , Meihao Liao , Guoren Wang

In this paper we study the problem of maintaining the strongly connected components of a graph in the presence of failures. In particular, we show that given a directed graph $G=(V,E)$ with $n=|V|$ and $m=|E|$, and an integer value $k\geq…

Data Structures and Algorithms · Computer Science 2017-04-25 Surender Baswana , Keerti Choudhary , Liam Roditty

Local graph neighborhood sampling is a fundamental computational problem that is at the heart of algorithms for node representation learning. Several works have presented algorithms for learning discrete node embeddings where graph nodes…

Machine Learning · Computer Science 2022-11-29 Konstantin Kutzkov

Embedding graphs in a geographical or latent space, i.e.\ inferring locations for vertices in Euclidean space or on a smooth manifold or submanifold, is a common task in network analysis, statistical inference, and graph visualization. We…

Computational Geometry · Computer Science 2022-05-18 Varsha Dani , Josep Díaz , Thomas P. Hayes , Cristopher Moore

Local search is a powerful heuristic in optimization and computer science, the complexity of which was studied in the white box and black box models. In the black box model, we are given a graph $G = (V,E)$ and oracle access to a function…

Computational Complexity · Computer Science 2023-08-16 Simina Brânzei , Davin Choo , Nicholas Recker