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In directed random graphs, in which edges can be assigned to have one of two directions, or perhaps both, the distance between two vertices $v$ and $v'$ can be computed along paths that are directed from $v$ to $v'$, or along paths that are…

Probability · Mathematics 2026-03-25 A. D. Barbour , Gesine Reinert

We propose graph-dependent implicit regularisation strategies for distributed stochastic subgradient descent (Distributed SGD) for convex problems in multi-agent learning. Under the standard assumptions of convexity, Lipschitz continuity,…

Machine Learning · Computer Science 2018-09-20 Dominic Richards , Patrick Rebeschini

The present work describes the asymptotic local shape of a graph drawn uniformly at random from all connected simple planar graphs with n labelled vertices. We establish a novel uniform infinite planar graph (UIPG) as quenched limit in the…

Probability · Mathematics 2019-08-15 Benedikt Stufler

Suppose that we are given an arbitrary graph $G=(V, E)$ and know that each edge in $E$ is going to be realized independently with some probability $p$. The goal in the stochastic matching problem is to pick a sparse subgraph $Q$ of $G$ such…

Data Structures and Algorithms · Computer Science 2020-02-28 Soheil Behnezhad , Mahsa Derakhshan , MohammadTaghi Hajiaghayi

We study the replacement paths problem in the $\mathsf{CONGEST}$ model of distributed computing. Given an $s$-$t$ shortest path $P$, the goal is to compute, for every edge $e$ in $P$, the shortest-path distance from $s$ to $t$ avoiding $e$.…

Data Structures and Algorithms · Computer Science 2025-08-28 Yi-Jun Chang , Yanyu Chen , Dipan Dey , Gopinath Mishra , Hung Thuan Nguyen , Bryce Sanchez

In Constrained Correlation Clustering, the goal is to cluster a complete signed graph in a way that minimizes the number of negative edges inside clusters plus the number of positive edges between clusters, while respecting hard constraints…

Data Structures and Algorithms · Computer Science 2025-11-05 Nate Veldt

The problem of network-constrained averaging is to compute the average of a set of values distributed throughout a graph G using an algorithm that can pass messages only along graph edges. We study this problem in the noisy setting, in…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-06-15 Nima Noorshams , Martin Wainwright

We prove novel convergence results for a stochastic proximal gradient algorithm suitable for solving a large class of convex optimization problems, where a convex objective function is given by the sum of a smooth and a possibly non-smooth…

Optimization and Control · Mathematics 2016-08-11 Lorenzo Rosasco , Silvia Villa , Bang Công Vũ

We show how to compute a 20-approximation of a minimum dominating set in a planar graph in a constant number of rounds in the LOCAL model of distributed computing. This improves on the previously best known approximation factor of 52, which…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-11-30 Ozan Heydt , Sebastian Siebertz , Alexandre Vigny

We investigate online algorithms for maximum (weight) independent set on graph classes with bounded inductive independence number like, e.g., interval and disk graphs with applications to, e.g., task scheduling and spectrum allocation. In…

Data Structures and Algorithms · Computer Science 2013-07-12 Oliver Göbel , Martin Hoefer , Thomas Kesselheim , Thomas Schleiden , Berthold Vöcking

We introduce the Graph TT (GTT) and Graph OSPA (GOSPA) metrics based on optimal assignment, which allow us to compare not only the edge structures but also general vertex and edge attributes of graphs of possibly different sizes. We argue…

Probability · Mathematics 2023-08-24 Dominic Schuhmacher , Leoni Carla Wirth

We consider the following stochastic matching problem on both weighted and unweighted graphs: A graph $G(V, E)$ along with a parameter $p \in (0, 1)$ is given in the input. Each edge of $G$ is realized independently with probability $p$.…

Data Structures and Algorithms · Computer Science 2018-11-09 Soheil Behnezhad , Alireza Farhadi , MohammadTaghi Hajiaghayi , Nima Reyhani

We study the complexity of local graph centrality estimation, with the goal of approximating the centrality score of a given target node while exploring only a sublinear number of nodes/arcs of the graph and performing a sublinear number of…

Data Structures and Algorithms · Computer Science 2018-08-07 Marco Bressan , Enoch Peserico , Luca Pretto

For any $\epsilon > 0$, we show that if $G$ is a regular graph on $n \gg_\epsilon 1$ vertices that is $\epsilon$-far (differs by at least $\epsilon n^2$ edges) from any Tur\'{a}n graph, then its second eigenvalue $\lambda_2$ satisfies…

Combinatorics · Mathematics 2025-07-15 Shengtong Zhang

Semi-random processes involve an adaptive decision-maker, whose goal is to achieve some predetermined objective in an online randomized environment. They have algorithmic implications in various areas of computer science, as well as…

Combinatorics · Mathematics 2020-09-29 Omri Ben-Eliezer , Lior Gishboliner , Dan Hefetz , Michael Krivelevich

We present a new fast all-pairs shortest path algorithm for unweighted graphs. In breadth-first search which is said to representative and fast in unweighted graphs, the average number of accesses to adjacent vertices (expressed by…

Data Structures and Algorithms · Computer Science 2019-08-20 Yasuo Yamane , Kenichi Kobayashi

The local minimum degree of a graph is the minimum degree that can be reached by means of local complementation. For any n, there exist graphs of order n which have a local minimum degree at least 0.189n, or at least 0.110n when restricted…

Discrete Mathematics · Computer Science 2016-08-18 David Cattanéo , Simon Perdrix

We adapt a recent algorithm by Ghaffari [SODA'16] for computing a Maximal Independent Set in the LOCAL model, so that it works in the significantly weaker BEEP model. For networks with maximum degree $\Delta$, our algorithm terminates…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-04-25 Stephan Holzer , Nancy Lynch

We analyze site percolation on directed and undirected graphs with site-dependent open-site probabilities. We construct upper bounds on cluster susceptibilities, vertex connectivity functions, and the expected number of simple open cycles…

Mathematical Physics · Physics 2016-10-18 Kathleen E. Hamilton , Leonid P. Pryadko

Diameter, radius and eccentricities are fundamental graph parameters, which are extensively studied in various computational settings. Typically, computing approximate answers can be much more efficient compared with computing exact…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-12-08 Bertie Ancona , Keren Censor-Hillel , Mina Dalirrooyfard , Yuval Efron , Virginia Vassilevska Williams