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Graph convolution is a fundamental building block for many deep neural networks on graph-structured data. In this paper, we introduce a simple, yet very effective graph convolutional network with skip connections for semi-supervised anomaly…

Machine Learning · Computer Science 2023-10-17 Mahsa Mesgaran , A. Ben Hamza

In a graph, a Clique-Stable Set separator (CS-separator) is a family $\mathcal{C}$ of cuts (bipartitions of the vertex set) such that for every clique $K$ and every stable set $S$ with $K \cap S = \emptyset$, there exists a cut $( W,W')$ in…

Combinatorics · Mathematics 2017-07-27 Nicolas Bousquet , Aurélie Lagoutte , Frédéric Maffray , Lucas Pastor

Discovering the underlying structures present in large real world graphs is a fundamental scientific problem. In this paper we show that a graph's clique tree can be used to extract a hyperedge replacement grammar. If we store an ordering…

Social and Information Networks · Computer Science 2016-08-11 Salvador Aguiñaga , Rodrigo Palacios , David Chiang , Tim Weninger

A good computer network is hard to disrupt. It is desired that the computer communication network remains connected even when some of the links or nodes fail. Since the communication links are expensive, one wants to achieve these goals…

Networking and Internet Architecture · Computer Science 2009-08-10 Kamalesh V. N , S. K. Srivatsa

Hypergraphs capture multi-way relationships in data, and they have consequently seen a number of applications in higher-order network analysis, computer vision, geometry processing, and machine learning. In this paper, we develop…

Metric Geometry · Mathematics 2023-02-06 Samir Chowdhury , Tom Needham , Ethan Semrad , Bei Wang , Youjia Zhou

Convexification techniques have gained increasing interest over the past decades. In this work, we apply a recently developed convexification technique for fractional programs by He, Liu and Tawarmalani (2024) to the problem of determining…

Optimization and Control · Mathematics 2024-10-04 Timotej Hrga , Melanie Siebenhofer , Angelika Wiegele

We suggest a reduction of the combinatorial problem of hypergraph partitioning to a continuous optimization problem.

Data Structures and Algorithms · Computer Science 2019-09-19 Alexander Mishchenko , Vladimir Manuilov , Chao You , Han Yang

Binary semantic segmentation in computer vision is a fundamental problem. As a model-based segmentation method, the graph-cut approach was one of the most successful binary segmentation methods thanks to its global optimality guarantee of…

Computer Vision and Pattern Recognition · Computer Science 2023-12-11 Hui Xie , Weiyu Xu , Ya Xing Wang , John Buatti , Xiaodong Wu

The aim of this paper is to generalize the notion of the coloring complex of a graph to hypergraphs. We present three different interpretations of those complexes -- a purely combinatorial one and two geometric ones. It is shown, that most…

Combinatorics · Mathematics 2012-05-01 Felix Breuer , Aaron Dall , Martina Kubitzke

A vertex whose removal in a graph $G$ increases the number of components of $G$ is called a cut vertex. For all $n,c$, we determine the maximum number of connected induced subgraphs in a connected graph with order $n$ and $c$ cut vertices,…

Combinatorics · Mathematics 2019-10-11 Audace A. V. Dossou-Olory

We present time-efficient distributed algorithms for decomposing graphs with large edge or vertex connectivity into multiple spanning or dominating trees, respectively. As their primary applications, these decompositions allow us to achieve…

Data Structures and Algorithms · Computer Science 2013-11-22 Keren Censor-Hillel , Mohsen Ghaffari , Fabian Kuhn

A hypergraph is a set V of vertices and a set of non-empty subsets of V, called hyperedges. Unlike graphs, hypergraphs can capture higher-order interactions in social and communication networks that go beyond a simple union of pairwise…

Data Structures and Algorithms · Computer Science 2012-02-02 Jianhang Gao , Qing Zhao , Wei Ren , Ananthram Swami , Ram Ramanathan , Amotz Bar-Noy

Disentanglement via mechanism sparsity was introduced recently as a principled approach to extract latent factors without supervision when the causal graph relating them in time is sparse, and/or when actions are observed and affect them…

Machine Learning · Statistics 2022-07-19 Sébastien Lachapelle , Simon Lacoste-Julien

A hypergraph is said to be $1$-Sperner if for every two hyperedges the smallest of their two set differences is of size one. We present several applications of $1$-Sperner hypergraphs and their structure to graphs. In particular, we…

Combinatorics · Mathematics 2018-05-30 Endre Boros , Vladimir Gurvich , Martin Milanič

The future of main memory appears to lie in the direction of new technologies that provide strong capacity-to-performance ratios, but have write operations that are much more expensive than reads in terms of latency, bandwidth, and energy.…

Data Structures and Algorithms · Computer Science 2017-10-10 Naama Ben-David , Guy E. Blelloch , Jeremy T. Fineman , Phillip B. Gibbons , Yan Gu , Charles McGuffey , Julian Shun

We show an improved parallel algorithm for decomposing an undirected unweighted graph into small diameter pieces with a small fraction of the edges in between. These decompositions form critical subroutines in a number of graph algorithms.…

Data Structures and Algorithms · Computer Science 2013-07-16 Gary L. Miller , Richard Peng , Shen Chen Xu

For many tracking and surveillance applications, background subtraction provides an effective means of segmenting objects moving in front of a static background. Researchers have traditionally used combinations of morphological operations…

Computer Vision and Pattern Recognition · Computer Science 2014-11-17 Nicholas R. Howe , Alexandra Deschamps

We give a characterization of distance--preserving subgraphs of Johnson graphs, i.e. of graphs which are isometrically embeddable into Johnson graphs (the Johnson graph $J(m,\Lambda)$ has the subsets of cardinality $m$ of a set $\Lambda$ as…

Combinatorics · Mathematics 2015-11-03 Victor Chepoi

Hypergraphs are important objects to model ternary or higher-order relations of objects, and have a number of applications in analysing many complex datasets occurring in practice. In this work we study a new heat diffusion process in…

Data Structures and Algorithms · Computer Science 2022-05-06 Peter Macgregor , He Sun

Hypergraph partitioning is a recurring NP-hard problem in engineering; its efficient solution at scale hinges on parallelism. This work proposes a GPU-centric algorithm for multi-level hypergraph partitioning aimed at a specific set of…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-05-21 Marco Ronzani , Cristina Silvano