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Related papers: Expander Graphs in Pure and Applied Mathematics

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Expander graphs have been, during the last five decades, the subject of a most fruitful interaction between pure mathematics and computer science, with influence and applications going both ways (cf. [Lub94], [HLW06], [Lub12] and the…

Group Theory · Mathematics 2017-12-08 Alexander Lubotzky

Expander graphs are widely used in communication problems and construction of error correcting codes. In such graphs, information gets through very quickly. Typically, it is not true for social or biological networks, though we may find a…

Combinatorics · Mathematics 2011-03-04 Marianna Bolla

We revisit the classical question of the relationship between the diameter of a graph and its expansion properties. One direction is well understood: expander graphs exhibit essentially the lowest possible diameter. We focus on the reverse…

Combinatorics · Mathematics 2017-11-23 Michael Dinitz , Michael Schapira , Gal Shahaf

A graph $G=(V,E)$ is called an expander if every vertex subset $U$ of size up to $|V|/2$ has an external neighborhood whose size is comparable to $|U|$. Expanders have been a subject of intensive research for more than three decades and…

Combinatorics · Mathematics 2019-01-29 Michael Krivelevich

Expander graphs in general, and Ramanujan graphs in particular, have been of great interest in the last three decades with many applications in computer science, combinatorics and even pure mathematics. In these notes we describe various…

Combinatorics · Mathematics 2013-01-15 Alexander Lubotzky

Expander decompositions of graphs have significantly advanced the understanding of many classical graph problems and led to numerous fundamental theoretical results. However, their adoption in practice has been hindered due to their…

Data Structures and Algorithms · Computer Science 2026-04-27 Kathrin Hanauer , Monika Henzinger , Robin Münk , Harald Räcke , Maximilian Vötsch

Expander graphs play a central role in graph theory and algorithms. With a number of powerful algorithmic tools developed around them, such as the Cut-Matching game, expander pruning, expander decomposition, and algorithms for decremental…

Data Structures and Algorithms · Computer Science 2022-12-12 Julia Chuzhoy

A graph G on n vertices is said to be extendable if G can be modified to form a new graph H on more than n vertices, while preserving the degrees of the vertices common to G and H. The added vertices all have the same degree and we define…

Combinatorics · Mathematics 2018-03-09 Ghurumuruhan Ganesan

Graph neural networks are deep neural networks designed for graphs with attributes attached to nodes or edges. The number of research papers in the literature concerning these models is growing rapidly due to their impressive performance on…

Machine Learning · Computer Science 2024-12-30 James H. Tanis , Chris Giannella , Adrian V. Mariano

A graph is a data structure composed of dots (i.e. vertices) and lines (i.e. edges). The dots and lines of a graph can be organized into intricate arrangements. The ability for a graph to denote objects and their relationships to one…

Data Structures and Algorithms · Computer Science 2010-09-07 Marko A. Rodriguez , Peter Neubauer

In modern mathematics, graphs figure as one of the better-investigated class of mathematical objects. Various properties of graphs, as well as graph-processing algorithms, can be useful if graphs of a certain kind are used as denotations…

Logic in Computer Science · Computer Science 2007-05-23 Alex Shkotin

Graph is an important data representation which appears in a wide diversity of real-world scenarios. Effective graph analytics provides users a deeper understanding of what is behind the data, and thus can benefit a lot of useful…

Artificial Intelligence · Computer Science 2018-02-05 Hongyun Cai , Vincent W. Zheng , Kevin Chen-Chuan Chang

Efficient CNN designs like ResNets and DenseNet were proposed to improve accuracy vs efficiency trade-offs. They essentially increased the connectivity, allowing efficient information flow across layers. Inspired by these techniques, we…

Computer Vision and Pattern Recognition · Computer Science 2018-07-27 Ameya Prabhu , Girish Varma , Anoop Namboodiri

Graph neural networks operate on graph-structured data via exchanging messages along edges. One limitation of this message passing paradigm is the over-squashing problem. Over-squashing occurs when messages from a node's expanded receptive…

Machine Learning · Computer Science 2023-11-15 Thomas Christie , Yu He

We introduce a new concept, which we call partition expanders. The basic idea is to study quantitative properties of graphs in a slightly different way than it is in the standard definition of expanders. While in the definition of expanders…

Computational Complexity · Computer Science 2022-03-30 Dmytro Gavinsky , Pavel Pudlák

In the last decade it became apparent that a large number of the most interesting structures and phenomena of the world can be described by networks: separable elements, with connections (or interactions) between certain pairs of them.…

Combinatorics · Mathematics 2009-02-03 Laszlo Lovasz

Diagram semigroups are interesting algebraic and combinatorial objects, several types of them originating from questions in computer science and in physics. Here we describe diagram semigroups in a general framework and extend our…

Group Theory · Mathematics 2015-02-27 James East , Attila Egri-Nagy , Andrew R. Francis , James D. Mitchell

We obtain several sharp spectral bounds, approximations, and exact values for the isoperimetric number and related edge-expansion parameters of graphs. Our results focus on graph powers and on families of graphs with rich algebraic or…

Let $G=(V,E)$ be a finite graph. For $v\in V$ we denote by $G_v$ the subgraph of $G$ that is induced by $v$'s neighbor set. We say that $G$ is $(a,b)$-regular for $a>b>0$ integers, if $G$ is $a$-regular and $G_v$ is $b$-regular for every…

Combinatorics · Mathematics 2019-08-29 Michael Chapman , Nati Linial , Yuval Peled

Graphs are a representation of structured data that captures the relationships between sets of objects. With the ubiquity of available network data, there is increasing industrial and academic need to quickly analyze graphs with billions of…

Machine Learning · Computer Science 2023-07-28 Brandon Mayer , Anton Tsitsulin , Hendrik Fichtenberger , Jonathan Halcrow , Bryan Perozzi
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