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We investigate the two problems of computing the union join graph as well as computing the subset graph for acyclic hypergraphs and their subclasses. In the union join graph $G$ of an acyclic hypergraph $H$, each vertex of $G$ represents a…

Data Structures and Algorithms · Computer Science 2021-04-15 Arne Leitert

We study the problem of deleting the smallest set $S$ of vertices (resp. edges) from a given graph $G$ such that the induced subgraph (resp. subgraph) $G \setminus S$ belongs to some class $\mathcal{H}$. We consider the case where graphs in…

Data Structures and Algorithms · Computer Science 2018-10-24 Anupam Gupta , Euiwoong Lee , Jason Li , Pasin Manurangsi , Michał Włodarczyk

We prove interlacing inequalities between spectral minimal energies of metric graphs built on Dirichlet and standard Laplacian eigenvalues, as recently introduced in [Kennedy et al, arXiv:2005.01126]. These inequalities, which involve the…

Spectral Theory · Mathematics 2021-07-28 Matthias Hofmann , James B. Kennedy

We prove a new generalization of the higher-order Cheeger inequality for partitioning with buffers. Consider a graph $G=(V,E)$. The buffered expansion of a set $S \subseteq V$ with a buffer $B \subseteq V \setminus S$ is the edge expansion…

Data Structures and Algorithms · Computer Science 2023-08-22 Konstantin Makarychev , Yury Makarychev , Liren Shan , Aravindan Vijayaraghavan

Hypergraph partitioning is an important problem in machine learning, computer vision and network analytics. A widely used method for hypergraph partitioning relies on minimizing a normalized sum of the costs of partitioning hyperedges…

Machine Learning · Computer Science 2017-11-06 Pan Li , Olgica Milenkovic

Recently, a number of variants of the notion of cut-preserving hypergraph sparsification have been studied in the literature. These variants include directed hypergraph sparsification, submodular hypergraph sparsification, general notions…

Data Structures and Algorithms · Computer Science 2024-02-21 Sanjeev Khanna , Aaron L. Putterman , Madhu Sudan

In this paper, we characterize all graphs with eigenvectors of the signless Laplacian and adjacency matrices with components equal to $\{- 1, 0, 1\}.$ We extend the graph parameter max $k$-cut to square matrices and prove a general sharp…

Combinatorics · Mathematics 2022-11-29 Jorge Alencar , Leonardo de Lima , Vladimir Nikiforov

We answer three questions posed in a paper by Babson and Benjamini. They introduced a parameter $C_G$ for Cayley graphs $G$ that has significant application to percolation. For a minimal cutset of $G$ and a partition of this cutset into two…

Combinatorics · Mathematics 2020-05-11 Adam Timar

Modeling information that resides on vertices of large graphs is a key problem in several real-life applications, ranging from social networks to the Internet-of-things. Signal Processing on Graphs and, in particular, graph wavelets can…

Data Structures and Algorithms · Computer Science 2016-06-14 Arlei Silva , Xuan-Hong Dang , Prithwish Basu , Ambuj K Singh , Ananthram Swami

This paper describes a method for efficiently computing parallel transport of tangent vectors on curved surfaces, or more generally, any vector-valued data on a curved manifold. More precisely, it extends a vector field defined over any…

Graphics · Computer Science 2020-07-24 Nicholas Sharp , Yousuf Soliman , Keenan Crane

We consider the problem of partitioning the node set of a graph into $k$ sets of given sizes in order to \emph{minimize the cut} obtained using (removing) the $k$-th set. If the resulting cut has value $0$, then we have obtained a vertex…

Optimization and Control · Mathematics 2014-11-20 Ting Kei Pong , Hao Sun , Ningchuan Wang , Henry Wolkowicz

Spectral partitioning is a simple, nearly-linear time, algorithm to find sparse cuts, and the Cheeger inequalities provide a worst-case guarantee for the quality of the approximation found by the algorithm. Local graph partitioning…

Data Structures and Algorithms · Computer Science 2012-11-07 Shayan Oveis Gharan , Luca Trevisan

Hypergraphs are a generalization of graphs in which edges can connect any number of vertices. They allow the modeling of complex networks with higher-order interactions, and their spectral theory studies the qualitative properties that can…

Combinatorics · Mathematics 2021-12-01 Raffaella Mulas

Link prediction in graphs is studied by modeling the dyadic interactions among two nodes. The relationships can be more complex than simple dyadic interactions and could require the user to model super-dyadic associations among nodes. Such…

Social and Information Networks · Computer Science 2021-02-10 Deepak Maurya , Balaraman Ravindran

We obtain a lower bound on each entry of the principal eigenvector of a non-regular connected graph.

Combinatorics · Mathematics 2014-03-11 Felix Goldberg

A connected graph $G$ is of QE class if it admits a quadratic embedding in a Hilbert space, or equivalently if the distance matrix is conditionally negative definite, or equivalently if the quadratic embedding constant $\mathrm{QEC}(G)$ is…

Combinatorics · Mathematics 2018-02-06 Wojciech Młotkowski , Nobuaki Obata

Given a graph $G$, the maximal induced subgraphs problem asks to enumerate all maximal induced subgraphs of $G$ that belong to a certain hereditary graph class. While its optimization version, known as the minimum vertex deletion problem in…

Data Structures and Algorithms · Computer Science 2020-04-22 Yixin Cao

We develop a notion of containment for independent sets in hypergraphs. For every $r$-uniform hypergraph $G$, we find a relatively small collection $C$ of vertex subsets, such that every independent set of $G$ is contained within a member…

Combinatorics · Mathematics 2014-12-01 David Saxton , Andrew Thomason

We prove the Li-Yau gradient estimate for the heat kernel on graphs. The only assumption is a variant of the curvature-dimension inequality, which is purely local, and can be considered as a new notion of curvature for graphs. We compute…

Analysis of PDEs · Mathematics 2015-12-02 Frank Bauer , Paul Horn , Yong Lin , Gabor Lippner , Dan Mangoubi , Shing-Tung Yau

Normalized graph cut (NGC) has become a popular research topic due to its wide applications in a large variety of areas like machine learning and very large scale integration (VLSI) circuit design. Most of traditional NGC methods are based…

Machine Learning · Computer Science 2015-11-10 Cong Xie , Wu-Jun Li , Zhihua Zhang