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A spin system is a framework in which the vertices of a graph are assigned spins from a finite set. The interactions between neighbouring spins give rise to weights, so a spin assignment can also be viewed as a weighted graph homomorphism.…

Data Structures and Algorithms · Computer Science 2021-04-15 Andreas Galanis , Leslie Ann Goldberg , James Stewart

Graph partition is a key component to achieve workload balance and reduce job completion time in parallel graph processing systems. Among the various partition strategies, edge partition has demonstrated more promising performance in…

Data Structures and Algorithms · Computer Science 2020-12-18 Zhenyu Guo , Mingyu Xiao , Yi Zhou , Dongxiang Zhang , Kian-Lee Tan

Our goal is to efficiently compute low-dimensional latent coordinates for nodes in an input graph -- known as graph embedding -- for subsequent data processing such as clustering. Focusing on finite graphs that are interpreted as uniform…

Signal Processing · Electrical Eng. & Systems 2022-03-08 Fei Chen , Gene Cheung , Xue Zhang

In the realm of generative models for graphs, extensive research has been conducted. However, most existing methods struggle with large graphs due to the complexity of representing the entire joint distribution across all node pairs and…

Social and Information Networks · Computer Science 2024-05-15 Andreas Bergmeister , Karolis Martinkus , Nathanaël Perraudin , Roger Wattenhofer

Network (or Graph) Alignment Algorithms aims to reveal structural similarities among graphs. In particular Local Network Alignment Algorithms (LNAs) finds local regions of similarity among two or more networks. Such algorithms are in…

Social and Information Networks · Computer Science 2020-08-12 Pietro Hiram Guzzi

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

The Massive Parallel Computation (MPC) model is a theoretical framework for popular parallel and distributed platforms such as MapReduce, Hadoop, or Spark. We consider the task of computing a large matching or small vertex cover in this…

Data Structures and Algorithms · Computer Science 2018-07-24 Krzysztof Onak

Graph drawing addresses the problem of finding a layout of a graph that satisfies given aesthetic and understandability objectives. The most important objective in graph drawing is minimization of the number of crossings in the drawing, as…

Computational Geometry · Computer Science 2014-01-22 Mohamed A. El-Sayed , S. Abdel-Khalek , Hanan H. Amin

Motivated by applications of large-scale graph clustering, we study random-walk-based LOCAL algorithms whose running times depend only on the size of the output cluster, rather than the entire graph. All previously known such algorithms…

Data Structures and Algorithms · Computer Science 2013-11-08 Zeyuan Allen Zhu , Silvio Lattanzi , Vahab Mirrokni

Hopsets and spanners are fundamental graph structures, playing a key role in shortest path computation, distributed communication, and more. A (near-exact) hopset for a given graph $G$ is a (small) subset of weighted edges $H$ that when…

Data Structures and Algorithms · Computer Science 2022-11-15 Shimon Kogan , Merav Parter

We study the problem of estimating the maximum matching size in graphs whose edges are revealed in a streaming manner. We consider both insertion-only streams and dynamic streams and present new upper and lower bound results for both…

Data Structures and Algorithms · Computer Science 2017-01-17 Sepehr Assadi , Sanjeev Khanna , Yang Li

Given a graph $G$ of degree $k$ over $n$ vertices, we consider the problem of computing a near maximum cut or a near minimum bisection in polynomial time. For graphs of girth $2L$, we develop a local message passing algorithm whose…

Probability · Mathematics 2023-02-06 Ahmed El Alaoui , Andrea Montanari , Mark Sellke

Graph spanners and emulators are sparse structures that approximately preserve distances of the original graph. While there has been an extensive amount of work on additive spanners, so far little attention was given to weighted graphs.…

Data Structures and Algorithms · Computer Science 2021-03-02 Michael Elkin , Yuval Gitlitz , Ofer Neiman

We present a new approach for solving (minimum disagreement) correlation clustering that results in sublinear algorithms with highly efficient time and space complexity for this problem. In particular, we obtain the following algorithms for…

Data Structures and Algorithms · Computer Science 2021-09-30 Sepehr Assadi , Chen Wang

We introduce a method for sparsifying distributed algorithms and exhibit how it leads to improvements that go past known barriers in two algorithmic settings of large-scale graph processing: Massively Parallel Computation (MPC), and Local…

Data Structures and Algorithms · Computer Science 2018-07-18 Mohsen Ghaffari , Jara Uitto

Feature extraction is an essential task in graph analytics. These feature vectors, called graph descriptors, are used in downstream vector-space-based graph analysis models. This idea has proved fruitful in the past, with spectral-based…

Machine Learning · Computer Science 2023-04-11 Zohair Raza Hassan , Sarwan Ali , Imdadullah Khan , Mudassir Shabbir , Waseem Abbas

Motivated by the problem of routing reliably and scalably in a graph, we introduce the notion of a splicer, the union of spanning trees of a graph. We prove that for any bounded-degree n-vertex graph, the union of two random spanning trees…

Discrete Mathematics · Computer Science 2008-07-10 Navin Goyal , Luis Rademacher , Santosh Vempala

Resolving an open question from 2006, we prove the existence of light-weight bounded-degree spanners for unit ball graphs in the metrics of bounded doubling dimension, and we design a simple $\mathcal{O}(\log^*n)$-round distributed…

Computational Geometry · Computer Science 2022-11-08 David Eppstein , Hadi Khodabandeh

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

Balanced partitioning is often a crucial first step in solving large-scale graph optimization problems, e.g., in some cases, a big graph can be chopped into pieces that fit on one machine to be processed independently before stitching the…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-12-10 Kevin Aydin , MohammadHossein Bateni , Vahab Mirrokni