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Graph-based methods are known to be successful in many machine learning and pattern classification tasks. These methods consider semi-structured data as graphs where nodes correspond to primitives (parts, interest points, segments, etc.)…

Computer Vision and Pattern Recognition · Computer Science 2019-01-01 Anjan Dutta , Hichem Sahbi

Let $G=(V(G),E(G))$ be a simple graph with vertex set $V(G)$ and edge set $E(G)$. Let $S$ be a subset of $V(G)$, and let $B(S)$ be the set of neighbours of $S$ in $V(G) \setminus S$. The differential $\partial(S)$ of $S$ is defined as…

We present a novel method for graph partitioning, based on reinforcement learning and graph convolutional neural networks. Our approach is to recursively partition coarser representations of a given graph. The neural network is implemented…

Machine Learning · Computer Science 2021-06-30 Alice Gatti , Zhixiong Hu , Tess Smidt , Esmond G. Ng , Pieter Ghysels

The nodes of a graph existing in a cluster are more likely to connect to each other than with other nodes in the graph. Then revealing some information about some nodes, the structure of the graph (graph edges) provides this opportunity to…

Machine Learning · Computer Science 2020-11-17 Mohammad Esmaeili , Aria Nosratinia

Node classification and graph classification are two graph learning problems that predict the class label of a node and the class label of a graph respectively. A node of a graph usually represents a real-world entity, e.g., a user in a…

Computer Vision and Pattern Recognition · Computer Science 2019-04-11 Jia Li , Yu Rong , Hong Cheng , Helen Meng , Wenbing Huang , Junzhou Huang

In this paper, we introduce the notion of the containment graph of a family of sets and containment classes of graphs and posets. Let $Z$ be a family of nonempty sets. We call a (simple, finite) graph G = (V, E) a $Z$-containment graph…

Discrete Mathematics · Computer Science 2019-07-18 Martin Charles Golumbic , Edward R. Scheinerman

To every directed graph $E$ one can associate a \emph{graph inverse semigroup} $G(E)$, where elements roughly correspond to possible paths in $E$. These semigroups generalize polycylic monoids, and they arise in the study of Leavitt path…

Group Theory · Mathematics 2016-05-26 Z. Mesyan , J. D. Mitchell , M. Morayne , Y. H. Péresse

We present a semi-supervised learning framework based on graph embeddings. Given a graph between instances, we train an embedding for each instance to jointly predict the class label and the neighborhood context in the graph. We develop…

Machine Learning · Computer Science 2016-05-30 Zhilin Yang , William W. Cohen , Ruslan Salakhutdinov

Path and boundary-path groupoids of finitely aligned higher-rank graphs are often constructed using either filters or graph morphisms. We generalise the graph morphism approach to finitely aligned P-graphs where (Q, P) is a weakly…

Rings and Algebras · Mathematics 2025-09-18 Lisa Orloff Clark , Malcolm Jones

A simple graph $G=(V,E)$ is word-representable if there exists a word $w$ over the alphabet $V$ such that letters $x$ and $y$ alternate in $w$ iff $xy\in E$. Word-representable graphs generalize several important classes of graphs. A graph…

Combinatorics · Mathematics 2019-10-03 Özgür Akgün , Ian P. Gent , Sergey Kitaev , Hans Zantema

We study the percolation properties of graph partitioning on random regular graphs with N vertices of degree $k$. Optimal graph partitioning is directly related to optimal attack and immunization of complex networks. We find that for any…

Statistical Mechanics · Physics 2007-10-07 Gerald Paul , Reuven Cohen , Sameet Sreenivasan , Shlomo Havlin , H. Eugene Stanley

A mixed graph $G$ is a graph that consists of both undirected and directed edges. An orientation of $G$ is formed by orienting all the undirected edges of $G$, i.e., converting each undirected edge $\{u,v\}$ into a directed edge that is…

Data Structures and Algorithms · Computer Science 2024-04-15 Loukas Georgiadis , Dionysios Kefallinos , Evangelos Kosinas

Let $G$ be a group. We define the coprime graph of subgroups of $G$, denoted by $\mathcal P(G)$, is a graph whose vertex set is the set of all proper subgroups of $G$, and two distinct vertices are adjacent if and only if the order of the…

Group Theory · Mathematics 2015-12-08 R. Rajkumar , P. Devi

Graph states provide a powerful framework for describing multipartite entanglement in quantum information science. In their standard formulation, graph states are generated by controlled-$Z$ interactions and naturally encode symmetric…

Quantum Physics · Physics 2026-05-05 Matheus R. de Jesus , Eduardo O. C. Hoefel , Renato M. Angelo

We study graph realization problems from a distributed perspective and we study it in the node capacitated clique (NCC) model of distributed computing, recently introduced for representing peer-to-peer networks. We focus on two central…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-02-19 John Augustine , Keerti Choudhary , Avi Cohen , David Peleg , Sumathi Sivasubramaniam , Suman Sourav

Semi-transitive graphs, defined in \cite{hps98} as examples where ``uniform percolation" holds whenever $p>p_c$, are a large class of graphs more general than quasi-transitive graphs. Let $G$ be a semi-transitive graph with one end which…

Combinatorics · Mathematics 2023-07-21 Zhongyang Li

The availability of larger and larger graph datasets, growing exponentially over the years, has created several new algorithmic challenges to be addressed. Sequential approaches have become unfeasible, while interest on parallel and…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-03-26 Alessio Guerrieri , Alberto Montresor

An {\em ordered $r$-graph} is an $r$-uniform hypergraph whose vertex set is linearly ordered. Given $2\leq k\leq r$, an ordered $r$-graph $H$ is {\em interval} $k$-{\em partite} if there exist at least $k$ disjoint intervals in the ordering…

Combinatorics · Mathematics 2020-04-13 Zoltán F\" uredi , Tao Jiang , Alexandr Kostochka , Dhruv Mubayi , Jacques Verstraëte

Graph-based methods are known to be successful in many machine learning and pattern classification tasks. These methods consider semi-structured data as graphs where nodes correspond to primitives (parts, interest points, segments, etc.)…

Computer Vision and Pattern Recognition · Computer Science 2018-03-02 Anjan Dutta , Hichem Sahbi

Let $S=(G, \sigma)$ be a signed graph where $G=(V, E)$ is a graph called the underlying graph of $S$ and $\sigma:E(G) \rightarrow \{+,~-\}$. Let $f:V(G) \rightarrow \{1,2,\dots,|V(G)|\}$ such that $\sigma(uv)=+$ if and only if $f(u)$ and…

Combinatorics · Mathematics 2021-08-10 Mukti Acharya , Joseph Varghese Kureethara
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