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Data defined over a network have been successfully modelled by means of graph filters. However, although in many scenarios the connectivity of the network is known, e.g., smart grids, social networks, etc., the lack of well-defined…

Signal Processing · Electrical Eng. & Systems 2020-07-08 Alberto Natali , Mario Coutino , Geert Leus

We exhibit an analogy between the problem of pushing forward measurable sets under measure preserving maps and linear relaxations in combinatorialoptimization. We show how invariance of hyperfiniteness of graphings under local isomorphism…

Combinatorics · Mathematics 2021-02-17 László Lovász

This paper analyzes different online algorithms for the problem of assigning weights to edges in a fully-connected bipartite graph that minimizes the overall cost while satisfying constraints. Edges in this graph may disappear and reappear…

Computational Complexity · Computer Science 2011-05-03 Ankur Sahai

We present an approach to reduced-order modelling that builds off recent graph-theoretic work for representation, exploration, and analysis of computed states of physical systems (Banerjee et al., Comp. Meth. App. Mech. Eng., 351, 501-530,…

Numerical Analysis · Mathematics 2022-12-21 Matthew Duschenes , Siddhartha Srivastava , Krishna Garikipati

We explore a new form of DFT, which we call the Polynomial Transform. It functions over finite fields, and a size $n$ transform takes $O(n)$ operations. In the multitape Turing machine model, it allows us to multiply two $n$ bit numbers in…

Data Structures and Algorithms · Computer Science 2019-12-11 Matt Groff

Suppose a finite, unweighted, combinatorial graph $G = (V,E)$ is the union of several (degree-)regular graphs which are then additionally connected with a few additional edges. $G$ will then have only a small number of vertices $v \in V$…

Combinatorics · Mathematics 2023-10-25 Tony Zeng

In a bidirected graph an edge has a direction at each end, so bidirected graphs generalize directed graphs. We generalize the definitions of transitive closure and transitive reduction from directed graphs to bidirected graphs by…

Combinatorics · Mathematics 2021-06-16 Ouahiba Bessouf , Abdelkader Khelladi , Thomas Zaslavsky

We propose an approach to learning with graph-structured data in the problem domain of graph classification. In particular, we present a novel type of readout operation to aggregate node features into a graph-level representation. To this…

Machine Learning · Computer Science 2021-05-18 Christoph D. Hofer , Florian Graf , Bastian Rieck , Marc Niethammer , Roland Kwitt

Weight-balanced and doubly stochastic digraphs are two classes of digraphs that play an essential role in a variety of cooperative control problems, including formation control, distributed averaging, and optimization. We refer to a digraph…

Optimization and Control · Mathematics 2011-10-19 Bahman Gharesifard , Jorge Cortes

Current graph neural networks (GNNs) lack generalizability with respect to scales (graph sizes, graph diameters, edge weights, etc..) when solving many graph analysis problems. Taking the perspective of synthesizing graph theory programs,…

Machine Learning · Computer Science 2020-10-27 Hao Tang , Zhiao Huang , Jiayuan Gu , Bao-Liang Lu , Hao Su

Let ${\cal G}=(G,w)$ be a weighted simple finite connected graph, that is, let $G$ be a simple finite connected graph endowed with a function $w$ from the set of the edges of $G$ to the set of real numbers. For any subgraph $G'$ of $G$, we…

Combinatorics · Mathematics 2014-12-18 Elena Rubei

This paper presents a unified approach for localizing some relevant graph topological indices via majorization techniques. Through this method, old and new bounds are derived and numerical examples are provided, showing how former results…

Combinatorics · Mathematics 2015-03-27 Alessandra Cornaro , Monica Bianchi , Anna Torriero

We consider a new semidefinite programming relaxation for directed edge expansion, which is obtained by adding triangle inequalities to the reweighted eigenvalue formulation. Applying the matrix multiplicative weight update method to this…

Data Structures and Algorithms · Computer Science 2023-06-16 Lap Chi Lau , Kam Chuen Tung , Robert Wang

We consider the following problem: for a given graph $G$ and two integers $k$ and $d$, can we apply a fixed graph operation at most $k$ times in order to reduce a given graph parameter $\pi$ by at least $d$? We show that this problem is…

Combinatorics · Mathematics 2022-10-20 Felicia Lucke , Felix Mann

We develop a theory of $\times$-homotopy, fundamental groupoids and covering spaces that apply to non-simple graphs, generalizing existing results for simple graphs. We prove that $\times$-homotopies from finite graphs can be decomposed…

Combinatorics · Mathematics 2026-03-17 Tien Chih , Laura Scull

We develop a theory of rewriting for structured cospans in order to extend compositional methods for modeling open networks. First, we introduce a category whose objects are structured cospans, and establish conditions under which it is…

Category Theory · Mathematics 2026-04-06 Daniel Cicala

Graph polynomials encode fundamental combinatorial invariants of graphs. Their computation is investigated using tree and path decomposition frameworks, with formal definitions of treewidth, k-trees, and pathwidth establishing the…

Discrete Mathematics · Computer Science 2025-09-29 Mehul Bafna , Shaghik Amirian

Let $G=(V,E)$ be a finite connected graph along with a coloring of the vertices of $G$ using the colors in a given set $X$. In this paper, we introduce multi-color forcing, a generalization of zero-forcing on graphs, and give conditions in…

Combinatorics · Mathematics 2019-12-05 Chassidy Bozeman , Pamela E. Harris , Neel Jain , Ben Young , Teresa Yu

We study the parameterized complexity of Split Contraction and Threshold Contraction. In these problems we are given a graph G and an integer k and asked whether G can be modified into a split graph or a threshold graph, respectively, by…

Data Structures and Algorithms · Computer Science 2013-10-23 Leizhen Cai , Chengwei Guo

Transformer models have recently gained popularity in graph representation learning as they have the potential to learn complex relationships beyond the ones captured by regular graph neural networks. The main research question is how to…

Machine Learning · Computer Science 2023-10-31 Yuankai Luo , Veronika Thost , Lei Shi