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By prior work, it is known that any distributed graph algorithm that finds a maximal matching requires $\Omega(\log^* n)$ communication rounds, while it is possible to find a maximal fractional matching in $O(1)$ rounds in bounded-degree…

Data Structures and Algorithms · Computer Science 2023-07-18 Sameep Dahal , Jukka Suomela

We present improved distributed algorithms for triangle detection and its variants in the CONGEST model. We show that Triangle Detection, Counting, and Enumeration can be solved in $\tilde{O}(n^{1/2})$ rounds. In contrast, the previous…

Data Structures and Algorithms · Computer Science 2018-07-19 Yi-Jun Chang , Seth Pettie , Hengjie Zhang

Graph learning is often a necessary step in processing or representing structured data, when the underlying graph is not given explicitly. Graph learning is generally performed centrally with a full knowledge of the graph signals, namely…

Signal Processing · Electrical Eng. & Systems 2021-12-14 Isabela Cunha Maia Nobre , Mireille El Gheche , Pascal Frossard

Cographs are exactly the hereditarily well-colored graphs, i.e., the graphs for which a greedy vertex coloring of every induced subgraph uses only the minimally necessary number of colors $\chi(G)$. We show that greedy colorings are a…

We present near-optimal algorithms for detecting small vertex cuts in the CONGEST model of distributed computing. Despite extensive research in this area, our understanding of the vertex connectivity of a graph is still incomplete,…

Data Structures and Algorithms · Computer Science 2023-06-21 Merav Parter , Asaf Petruschka

Distributed proofs are mechanisms enabling the nodes of a network to collectivity and efficiently check the correctness of Boolean predicates on the structure of the network, or on data-structures distributed over the nodes (e.g., spanning…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-09-22 Laurent Feuilloley , Pierre Fraigniaud , Juho Hirvonen , Ami Paz , Mor Perry

Federated graph learning (FedGL) is an emerging federated learning (FL) framework that extends FL to learn graph data from diverse sources. FL for non-graph data has shown to be vulnerable to backdoor attacks, which inject a shared backdoor…

Cryptography and Security · Computer Science 2024-07-15 Yuxin Yang , Qiang Li , Jinyuan Jia , Yuan Hong , Binghui Wang

Distributed graph algorithms that separately optimize for either the number of rounds used or the total number of messages sent have been studied extensively. However, algorithms simultaneously efficient with respect to both measures have…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-05-18 Bernhard Haeupler , D. Ellis Hershkowitz , David Wajc

Minimal separators in graphs are an important concept in algorithmic graph theory. In particular, many problems that are NP-hard for general graphs are known to become polynomial-time solvable for classes of graphs with a polynomially…

Combinatorics · Mathematics 2019-06-03 Martin Milanič , Nevena Pivač

We provide a new constant factor approximation algorithm for the (connected) distance-$r$ dominating set problem on graph classes of bounded expansion. Classes of bounded expansion include many familiar classes of sparse graphs such as…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-06-08 Saeed Akhoondian Amiri , Patrice Ossona de Mendez , Roman Rabinovich , Sebastian Siebertz

Persistent homology (PH) has been widely applied to graph data to extract topological features. However, little attention has been paid to how different distance functions on a graph affect the resulting persistence barcodes and their…

Algebraic Topology · Mathematics 2026-02-17 Eunwoo Heo , Byeongchan Choi , Jae-Hun Jung

We consider the standard message passing model; we assume the system is fully synchronous: all processes start at the same time and time proceeds in synchronised rounds. In each round each vertex can transmit a different message of size…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-07-14 Y. Métivier , J. M. Robson , A. Zemmari

In the study of deterministic distributed algorithms it is commonly assumed that each node has a unique $O(\log n)$-bit identifier. We prove that for a general class of graph problems, local algorithms (constant-time distributed algorithms)…

Distributed, Parallel, and Cluster Computing · Computer Science 2013-12-24 Mika Göös , Juho Hirvonen , Jukka Suomela

Chordal graphs are the graphs in which every cycle of length at least four has a chord. A set $S$ is a vertex separator for vertices $a$ and $b$ if the removal of $S$ of the graph separates $a$ and $b$ into distinct connected components. A…

Discrete Mathematics · Computer Science 2018-03-22 Sérgio H. Nogueira , Vinicius F. dos Santos

Min orderings give a vertex ordering characterization, common to some graphs and digraphs such as interval graphs, complements of threshold tolerance graphs (known as co-TT graphs), and two-directional orthogonal ray graphs. An adjusted…

Discrete Mathematics · Computer Science 2018-10-16 Asahi Takaoka

This work examines the problem of graph learning over a diffusion network when data can be collected from a limited portion of the network (partial observability). The main question is to establish technical guarantees of consistent…

Statistics Theory · Mathematics 2020-06-08 Vincenzo Matta , Augusto Santos , Ali H. Sayed

A cocomparability graph is a graph whose complement admits a transitive orientation. An interval graph is the intersection graph of a family of intervals on the real line. In this paper we investigate the relationships between interval and…

Discrete Mathematics · Computer Science 2016-11-08 Jérémie Dusart , Michel Habib , Derek G. Corneil

We present deterministic constant-round protocols for the graph connectivity problem in the model where each of the $n$ nodes of a graph receives a row of the adjacency matrix, and broadcasts a single sublinear size message to all other…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-06-13 Pedro Montealegre , Ioan Todinca

This paper considers the problem of distributed optimization over time-varying graphs. For the case of undirected graphs, we introduce a distributed algorithm, referred to as DIGing, based on a combination of a distributed inexact gradient…

Optimization and Control · Mathematics 2017-03-21 Angelia Nedich , Alex Olshevsky , Wei Shi

We consider constrained variants of graph homomorphisms such as embeddings, monomorphisms, full homomorphisms, surjective homomorpshims, and locally constrained homomorphisms. We also introduce a new variation on this theme which derives…

Combinatorics · Mathematics 2014-04-23 Yangjing Long