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Among the novel metrics used to study the relative importance of nodes in complex networks, k-core decomposition has found a number of applications in areas as diverse as sociology, proteinomics, graph visualization, and distributed system…

Other Computer Science · Computer Science 2011-03-30 Alberto Montresor , Francesco De Pellegrini , Daniele Miorandi

We develop a framework for algorithms finding the diameter in graphs of bounded distance Vapnik-Chervonenkis dimension, in (parameterized) subquadratic time complexity. The class of bounded distance VC-dimension graphs is wide, including,…

Data Structures and Algorithms · Computer Science 2024-07-16 Lech Duraj , Filip Konieczny , Krzysztof Potępa

Decentralized optimization is a powerful paradigm that finds applications in engineering and learning design. This work studies decentralized composite optimization problems with non-smooth regularization terms. Most existing gradient-based…

Optimization and Control · Mathematics 2019-10-29 Sulaiman A. Alghunaim , Kun Yuan , Ali H. Sayed

Point clouds are an increasingly relevant data type but they are often corrupted by noise. We propose a deep neural network based on graph-convolutional layers that can elegantly deal with the permutation-invariance problem encountered by…

Computer Vision and Pattern Recognition · Computer Science 2020-07-07 Francesca Pistilli , Giulia Fracastoro , Diego Valsesia , Enrico Magli

Normalized-cut graph partitioning aims to divide the set of nodes in a graph into $k$ disjoint clusters to minimize the fraction of the total edges between any cluster and all other clusters. In this paper, we consider a fair variant of the…

Machine Learning · Computer Science 2023-10-10 Jia Li , Yanhao Wang , Arpit Merchant

We propose a new algorithm for finding the center of a graph, as well as the rank of each node in the hierarchy of distances to the center. In other words, our algorithm allows to partition the graph according to nodes distance to the…

Data Structures and Algorithms · Computer Science 2019-10-08 Frédéric Protin

We investigate efficient learning from higher-order graph convolution and learning directly from adjacency matrices for node classification. We revisit the scaled graph residual network and remove ReLU activation from residual layers and…

Machine Learning · Computer Science 2022-09-13 Kishan Wimalawarne , Taiji Suzuki

We consider three variants of the problem of finding a maximum weight restricted $2$-matching in a subcubic graph $G$. (A $2$-matching is any subset of the edges such that each vertex is incident to at most two of its edges.) Depending on…

Data Structures and Algorithms · Computer Science 2021-01-01 Katarzyna Paluch , Mateusz Wasylkiewicz

Extraction of a high-fidelity 3D medial axis is a crucial operation in CAD. When dealing with a polygonal model as input, ensuring accuracy and tidiness becomes challenging due to discretization errors inherent in the mesh surface.…

Graphics · Computer Science 2024-11-12 Pengfei Wang , Jiantao Song , Lei Wang , Shiqing Xin , Dongming Yan , Shuangmin Chen , Changhe Tu , Wenping Wang

Spatial graphs are particular graphs for which the nodes are localized in space (e.g., public transport network, molecules, branching biological structures). In this work, we consider the problem of spatial graph reduction, that aims to…

Machine Learning · Statistics 2026-03-10 Anna Calissano , Etienne Lasalle

Some skew-symmetrizable integer exchange matrices are associated to ideal (tagged) triangulations of marked bordered surfaces. These exchange matrices admits unfoldings to skew-symmetric matrices. We develop an combinatorial algorithm that…

Combinatorics · Mathematics 2012-02-07 Weiwen Gu

Tensor diagonalization means transforming a given tensor to an exactly or nearly diagonal form through multiplying the tensor by non-orthogonal invertible matrices along selected dimensions of the tensor. It is generalization of approximate…

Numerical Analysis · Computer Science 2016-07-04 Petr Tichavsky , Anh Huy Phan , Andrzej Cichocki

We describe an infinite family of edge-decompositions of complete graphs into two graphs, each of which triangulate the same orientable surface. Previously, such decompositions had only been known for only a few complete graphs. These…

Combinatorics · Mathematics 2021-11-24 Timothy Sun

We present an algorithm that enumerates all the minimal triangulations of a graph in incremental polynomial time. Consequently, we get an algorithm for enumerating all the proper tree decompositions, in incremental polynomial time, where…

Data Structures and Algorithms · Computer Science 2023-07-28 Nofar Carmeli , Batya Kenig , Benny Kimelfeld , Markus Kröll

We introduce a dense counterpart of graph degeneracy, which extends the recently-proposed invariant symmetric difference. We say that a graph has sd-degeneracy (for symmetric-difference degeneracy) at most $d$ if it admits an elimination…

Data Structures and Algorithms · Computer Science 2024-05-16 Édouard Bonnet , Julien Duron , John Sylvester , Viktor Zamaraev

A 2-club is a graph of diameter at most two. In the decision version of the parametrized {\sc 2-Club Cluster Edge Deletion} problem, an undirected graph $G$ is given along with an integer $k\geq 0$ as parameter, and the question is whether…

Data Structures and Algorithms · Computer Science 2021-07-05 Faisal N. Abu-Khzam , Norma Makarem , Maryam Shehab

We use the recently proposed node decimation algorithm for blocking dynamical geometries to investigate a class of models, with central charge greater than unity, coupled to 2D gravity. We demonstrate that the blocking preserves the fractal…

High Energy Physics - Lattice · Physics 2009-10-28 E. Gregory , S. M. Catterall , G. Thorleifsson

Triangulated meshes have become ubiquitous discrete-surface representations. In this paper we address the problem of how to maintain the manifold properties of a surface while it undergoes strong deformations that may cause topological…

Computer Vision and Pattern Recognition · Computer Science 2020-12-11 Andrei Zaharescu , Edmond Boyer , Radu Horaud

This work considers clustering nodes of a largely incomplete graph. Under the problem setting, only a small amount of queries about the edges can be made, but the entire graph is not observable. This problem finds applications in…

Machine Learning · Computer Science 2021-10-04 Shahana Ibrahim , Xiao Fu

Non-local self-similarity is well-known to be an effective prior for the image denoising problem. However, little work has been done to incorporate it in convolutional neural networks, which surpass non-local model-based methods despite…

Image and Video Processing · Electrical Eng. & Systems 2023-07-19 Diego Valsesia , Giulia Fracastoro , Enrico Magli