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We study strongly convex distributed optimization problems where a set of agents are interested in solving a separable optimization problem collaboratively. In this paper, we propose and study a two time-scale decentralized gradient descent…

Optimization and Control · Mathematics 2022-08-16 Hadi Reisizadeh , Behrouz Touri , Soheil Mohajer

For analysing real-world networks, graph representation learning is a popular tool. These methods, such as a graph autoencoder (GAE), typically rely on low-dimensional representations, also called embeddings, which are obtained through…

Machine Learning · Computer Science 2024-02-05 Ruikang Ouyang , Andrew Elliott , Stratis Limnios , Mihai Cucuringu , Gesine Reinert

A degeneration of a smooth projective curve to a strongly stable curve gives rise to a specialization map from divisors on curves to divisors on graphs. In this paper we show that this specialization behaves well under the presence of real…

Algebraic Geometry · Mathematics 2010-05-20 Marc Coppens

Topological metrics of graphs provide a natural way to describe the prominent features of various types of networks. Graph metrics describe the structure and interplay of graph edges and have found applications in many scientific fields. In…

Data Structures and Algorithms · Computer Science 2018-06-21 Loukianos Spyrou , Javier Escudero

Functional graphs (FGs) model the graph structures used to analyse the behaviour of functions from a discrete set to itself. In turn, such functions are used to study real complex phenomena evolving in time. As the systems involved can be…

Dynamical Systems · Mathematics 2024-04-05 François Doré , Enrico Formenti , Antonio E. Porreca , Sara Riva

We investigate connections between the symmetries (automorphisms) of a graph and its spectral properties. Whenever a graph has a symmetry, i.e. a nontrivial automorphism $\phi$, it is possible to use $\phi$ to decompose any matrix…

Combinatorics · Mathematics 2016-10-07 Wayne Barrett , Amanda Francis , Ben Webb

Can graph neural networks generalize to graphs that are different from the graphs they were trained on, e.g., in size? In this work, we study this question from a theoretical perspective. While recent work established such transferability…

Machine Learning · Computer Science 2023-06-08 Thien Le , Stefanie Jegelka

Graphs are used in many disciplines to model the relationships that exist between objects in a complex discrete system. Researchers may wish to compare a network of interest to a "typical" graph from a family (or ensemble) of graphs which…

Combinatorics · Mathematics 2025-08-08 Catherine Greenhill

We use exponential start time clustering to design faster and more work-efficient parallel graph algorithms involving distances. Previous algorithms usually rely on graph decomposition routines with strict restrictions on the diameters of…

Data Structures and Algorithms · Computer Science 2015-06-25 Gary L. Miller , Richard Peng , Adrian Vladu , Shen Chen Xu

A theta is a graph formed by three paths between the same pair of distinct vertices so that the union of any two of the paths induces a hole. A wheel is a graph formed by a hole and a node that has at least 3 neighbors in the hole. In this…

Combinatorics · Mathematics 2023-10-23 Marko Radovanović , Nicolas Trotignon , Kristina Vušković

We present a general method of designing fast approximation algorithms for cut-based minimization problems in undirected graphs. In particular, we develop a technique that given any such problem that can be approximated quickly on trees,…

Data Structures and Algorithms · Computer Science 2010-11-09 Aleksander Madry

K-core decomposition is a commonly used metric to analyze graph structure or study the relative importance of nodes in complex graphs. Recent years have seen rapid growth in the scale of the graph, especially in industrial settings. For…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-01-03 Shicheng Gao , Jie Xu , Xiaosen Li , Fangcheng Fu , Wentao Zhang , Wen Ouyang , Yangyu Tao , Bin Cui

Many real life networks present an average path length logarithmic with the number of nodes and a degree distribution which follows a power law. Often these networks have also a modular and self-similar structure and, in some cases -…

Statistical Mechanics · Physics 2009-02-26 Alicia Miralles , Lichao Chen , Zhongzhi Zhang , Francesc Comellas

In this paper, we develop semi-external and external memory algorithms for graph partitioning and clustering problems. Graph partitioning and clustering are key tools for processing and analyzing large complex networks. We address both…

Data Structures and Algorithms · Computer Science 2014-09-24 Yaroslav Akhremtsev , Peter Sanders , Christian Schulz

Many real life networks present an average path length logarithmic with the number of nodes and a degree distribution which follows a power law. Often these networks have also a modular and self-similar structure and, in some cases -…

Physics and Society · Physics 2010-02-17 Alicia Miralles , Francesc Comellas , Lichao Chen , Zhongzhi Zhang

Local complement is a graph operation formalized by Bouchet which replaces the neighborhood of a chosen vertex with its edge-complement. This operation induces an equivalence relation on graphs; determining the size of the resulting…

Combinatorics · Mathematics 2026-03-02 Nicholas Connolly , Shin Nishio , Kae Nemoto

While finite graphs have tree-decompositions that efficiently distinguish all their tangles, locally finite graphs with thick ends need not have such tree-decompositions. We show that every locally finite graph without thick ends admits…

Combinatorics · Mathematics 2024-03-25 Raphael W. Jacobs , Paul Knappe

We generalise structure tree theory, which is based on removing finitely many edges, to removing finitely many vertices. This gives a significant generalization of Tutte's tree decomposition of 2-connected graphs into 3-connected blocks.…

Group Theory · Mathematics 2015-01-05 M. J. Dunwoody , B. Krön

Classes of graphs with bounded expansion are a generalization of both proper minor closed classes and degree bounded classes. Such classes are based on a new invariant, the greatest reduced average density (grad) of G with rank r,…

Combinatorics · Mathematics 2007-05-23 Jaroslav Nesetril , Patrice Ossona De Mendez

Given a set of detections, detected at each time instant independently, we investigate how to associate them across time. This is done by propagating labels on a set of graphs, each graph capturing how either the spatio-temporal or the…

Computer Vision and Pattern Recognition · Computer Science 2015-12-02 Amit Kumar K. C. , Laurent Jacques , Christophe De Vleeschouwer
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