Results 181 to 190 of about 6,572,416 (223)

FedGCN: Convergence-Communication Tradeoffs in Federated Training of Graph Convolutional Networks

Neural Information Processing Systems, 2022
Methods for training models on graphs distributed across multiple clients have recently grown in popularity, due to the size of these graphs as well as regulations on keeping data where it is generated.
Yuhang Yao, Weizhao Jin, Srivatsan Ravi, Carlee Joe-Wong   +3 more
semanticscholar   +1 more source

Enhancing conservation network design with graph-theory and a measure of protected area effectiveness: Refining wildlife corridors in Belize, Central America

Landscape and Urban Planning, 2018
Maintaining connectivity among remaining natural areas has become increasingly important to ameliorate the negative effects of habitat loss and fragmentation on wildlife populations.
Maarten Hofman, M. Hayward, M. Kelly, N. Balkenhol   +3 more
semanticscholar   +1 more source

MMGCN: Multi-modal Graph Convolution Network for Personalized Recommendation of Micro-video

ACM Multimedia, 2019
Personalized recommendation plays a central role in many online content sharing platforms. To provide quality micro-video recommendation service, it is of crucial importance to consider the interactions between users and items (i.e. micro-videos) as well
Yin-wei Wei, Xiang Wang, Liqiang Nie, Xiangnan He, Richang Hong, Tat-Seng Chua   +5 more
semanticscholar   +1 more source

Graph classification based on structural features of significant nodes and spatial convolutional neural networks

Neurocomputing, 2021
Many real-world problems can be abstracted into graph classification problems. Recently, graph convolutional networks have achieved great success in the task of node classification and link prediction.
Tinghuai Ma, Hongmei Wang, Lejun Zhang, Y. Tian, N. Al-Nabhan   +4 more
semanticscholar   +1 more source

A Comprehensive Survey on Spectral Clustering with Graph Structure Learning

arXiv.org
Spectral clustering is a powerful technique for clustering high-dimensional data, utilizing graph-based representations to detect complex, non-linear structures and non-convex clusters.
Kamal Berahmand, Farid Saberi-Movahed, Razieh Sheikhpour, Yuefeng Li, Mahdi Jalili   +4 more
semanticscholar   +1 more source

Closeness Centrality on Uncertain Graphs

ACM Transactions on the Web, 2023
Centrality is a family of metrics for characterizing the importance of a vertex in a graph. Although a large number of centrality metrics have been proposed, a majority of them ignores uncertainty in graph data. In this article, we formulate closeness centrality on uncertain graphs and define the batch closeness centrality evaluation ...
Zhenfang Liu, Jianxiong Ye, Zhaonian Zou
openaire   +1 more source

Centrality measure in graphs

Journal of Mathematical Chemistry, 2010
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire   +2 more sources

Graph Theory Analysis of Functional Connectivity in Major Depression Disorder With High-Density Resting State EEG Data

IEEE transactions on neural systems and rehabilitation engineering, 2019
Existing studies have shown functional brain networks in patients with major depressive disorder (MDD) have abnormal network topology structure. But the methods to construct brain network still exist some issues to be solved.
Shuting Sun, Xiaowei Li, Jing Zhu, Ying Wang, Rong La, Xuemin Zhang, Liuqing Wei, Bin Hu   +7 more
semanticscholar   +1 more source

On the centrality in a graph

Scandinavian Journal of Psychology, 1974
Abstract.— The paper considers the concept of centrality in an undirected graph. A system of axioms and an index for centrality satisfying the axioms are presented. The index is based on the degrees of the vertices in a given undirected graph, and it will enlarge the class of comparable graphs with respect to a centrality measure.
openaire   +2 more sources

CLOSENESS CENTRALITY IN GRAPH PRODUCTS

Advances and Applications in Discrete Mathematics, 2023
Eballe, R. G., Balingit, C. M. R., Cabahug, I. S. jun., Flores, A. L. V., Lumpayao, S. M. B., Peñalosa, B. D., Tampipi, G. A. L., Villarta, C. A.   +7 more
openaire   +1 more source