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检索条件"主题词=Non-Backtracking Matrix"
14 条 记 录,以下是1-10 订阅
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Limiting empirical spectral distribution for the non-backtracking matrix of an Erdos-Renyi random graph
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COMBINATORICS PROBABILITY & COMPUTING 2023年 第6期32卷 956-973页
作者: Wang, Ke Wood, Philip Matchett Hong Kong Univ Sci & Technol Dept Math Kowloon Hong Kong Peoples R China Harvard Univ Dept Math Cambridge MA 02138 USA
In this note, we give a precise description of the limiting empirical spectral distribution for the non-backtracking matrices for an Erdos-Renyi graph G(n, p) assuming np / log n tends to infinity. We show that derand... 详细信息
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Efficient Algorithm Based on non-backtracking matrix for Community Detection in Signed Networks
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IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING 2022年 第4期9卷 2200-2211页
作者: Zhong, Zhaoyue Wang, Xiangrong Qu, Cunquan Wang, Guanghui Shandong Univ Sch Math Jinan 250100 Peoples R China Southern Univ Sci & Technol Inst Future Networks Shenzhen 518055 Peoples R China Peng Cheng Lab Res Ctr Networks & Commun Shenzhen 518066 Peoples R China Shandong Univ Data Sci Inst Jinan 250100 Peoples R China
Community detection or clustering is a crucial task for understanding the structure of complex systems. In some networks, nodes are permitted to be linked by either "positive" or "negative" edges;s... 详细信息
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Minimizing Spectral Radius of non-backtracking matrix by Edge Removal  21
Minimizing Spectral Radius of Non-Backtracking Matrix by Edg...
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30th ACM International Conference on Information and Knowledge Management (CIKM)
作者: Zhang, Zuobai Zhang, Zhongzhi Chen, Guanrong Fudan Univ Shanghai Peoples R China City Univ Hong Kong Hong Kong Peoples R China
The spectral radius of the non-backtracking matrix for an undirected graph plays an important role in various dynamic processes running on the graph. For example, its reciprocal provides an excellent approximation of ... 详细信息
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Analysis of the susceptible-infected-susceptible epidemic dynamics in networks via the non-backtracking matrix
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IMA JOURNAL OF APPLIED MATHEMATICS 2020年 第2期85卷 214-230页
作者: Masuda, Naoki Preciado, Victor M. Ogura, Masaki Univ Bristol Dept Engn Math Woodland Rd Bristol BS8 1UB Avon England Univ Buffalo State Univ New York Dept Math Buffalo NY 14260 USA Univ Buffalo State Univ New York Computat & Data Enabled Sci & Engn Program Buffalo NY 14260 USA Univ Penn Dept Elect & Syst Engn Philadelphia PA 19104 USA Univ Penn Appl Math & Computat Sci Philadelphia PA 19104 USA Nara Inst Sci & Technol Div Informat Sci Ikoma Nara 6300192 Japan Osaka Univ Grad Sch Informat Sci & Technol Suita Osaka 5650871 Japan
We study the stochastic susceptible-infected-susceptible model of epidemic processes on finite directed and weighted networks with arbitrary structure. We present a new lower bound on the exponential rate at which the... 详细信息
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Targeted influence maximization in complex networks
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PHYSICA D-nonLINEAR PHENOMENA 2023年 第1期446卷
作者: Zhang, Renquan Wang, Xiaolin Pei, Sen Dalian Univ Technol Sch Math Sci Dalian 116024 Peoples R China Columbia Univ Mailman Sch Publ Hlth Dept Environm Hlth Sci New York NY 10032 USA
Many real-world applications based on spreading processes in complex networks aim to deliver information to specific target nodes. However, it remains challenging to optimally select a set of spreaders to initiate the... 详细信息
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Spectral theory of the non-backtracking Laplacian for graphs
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DISCRETE MATHEMATICS 2023年 第10期346卷
作者: Jost, Juergen Mulas, Raffaella Torres, Leo Max Planck Inst Math Sci Leipzig Germany Santa Fe Inst Sci Complex Santa Fe NM USA Vrije Univ Amsterdam Amsterdam Netherlands
We introduce a non-backtracking Laplace operator for graphs and we investigate its spectral properties. With the use of both theoretical and computational techniques, we show that the spectrum of this operator capture... 详细信息
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non-backtracking spectra of weighted inhomogeneous random graphs
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Mathematical Statistics and Learning 2022年 第3-4期5卷 201-271页
作者: Stephan, Ludovic Massoulié, Laurent Information Learning and Physics (IdePHICS) lab École Polytechnique Fédérale de Lausanne (EPFL) Lausanne 1015 Switzerland Inria Paris – Département d’informatique de l’ENS PSL Research University Paris 75012 France
We study a model of random graphs where each edge is drawn independently (but not necessarily identically distributed) from the others, and then assigned a random weight. When the mean degree of such a graph is low, i... 详细信息
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Detecting the number of clusters in a network
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JOURNAL OF COMPLEX NETWORKS 2020年 第6期8卷
作者: Budel, Gabriel Van Mieghem, Piet Delft Univ Technol Fac Elect Engn Math & Comp Sci Delft Netherlands
Many clustering algorithms for complex networks depend on the choice for the number of clusters and it is often unclear how to make this choice. The number of eigenvalues located outside a circle in the spectrum of th... 详细信息
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backtracking activation impacts the criticality of excitable networks
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NEW JOURNAL OF PHYSICS 2020年 第1期22卷 1-1页
作者: Zhang, Renquan Quan, Guoyi Wang, Jiannan Pei, Sen Dalian Univ Technol Sch Math Sci Dalian 116024 Peoples R China Beihang Univ Res Inst Frontier Sci Beijing 100191 Peoples R China Minist Educ Key Lab Math Informat & Behav Semant Beijing Peoples R China Columbia Univ Mailman Sch Publ Hlth Dept Environm Hlth Sci New York NY 10032 USA
Networks of excitable elements are widely used to model real-world biological and social systems. The dynamic range of an excitable network quantifies the range of stimulus intensities that can be robustly distinguish... 详细信息
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Length Spectrum Theory, non-backtracking Cycles, and Two Graph Analysis Tasks  2
Length Spectrum Theory, Non-backtracking Cycles, and Two Gra...
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2nd ACM SIGMOD Joint International Workshop on Graph Data Management Experiences and Systems (GRADES) / Workshop on Network Data Analytics (NDA)
作者: Eliassi-Rad, Tina Northeastern Univ Boston MA 02115 USA
Two basic tasks in graph analysis are: (1) computing the distance between two graphs and (2) embedding of the graph elements (i.e., nodes or links) into a lower-dimensional space. The former task has numerous applicat... 详细信息
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