Zobrazeno 1 - 10
of 11
pro vyhledávání: '"Ping-En Lu"'
Publikováno v:
IEEE Transactions on Computational Social Systems. :1-18
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d86bfe2eeba8a4e2be8efdfa3f22dfb3
https://doi.org/10.1109/tcss.2022.3181739
https://doi.org/10.1109/tcss.2022.3181739
Autor:
Ping-En Lu, Cheng-Shang Chang
Publikováno v:
ACM SIGMETRICS Performance Evaluation Review. 48:3-5
Graph Convolutional Networks (GCN) have been very popular for the network embedding problem that maps nodes in a graph to vectors in a Euclidean space. In this short paper, we show that a special class of GCNs compute approximations of dominant eigen
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9a65b5368fde27f848dc49fcd07293c5
https://doi.org/10.1145/3439602.3439605
https://doi.org/10.1145/3439602.3439605
Publikováno v:
IEEE Transactions on Network Science and Engineering. 6:684-697
In this paper, we conduct centrality analysis and community detection for attributed networks. An attributed network, as a generalization of a graph, has node attributes and edge attributes that represent the “features” of nodes and edges. Tradit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7aebc2942e636cb8ecd56b812a7790c1
https://doi.org/10.1109/tnse.2018.2870671
https://doi.org/10.1109/tnse.2018.2870671
Publikováno v:
IEEE Transactions on Computational Social Systems. 6:968-980
Centrality analysis has been a very important research topic in online social networks. Traditionally, centrality analysis is carried out for a specific network. In this article, we conduct centrality analysis in random networks. For this, we conside
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cf761170f9c37f4f83347bb233587f7d
https://doi.org/10.1109/tcss.2019.2935306
https://doi.org/10.1109/tcss.2019.2935306
Publikováno v:
IEEE Transactions on Network Science and Engineering
In this paper, we conduct mathematical and numerical analyses to address the following crucial questions for COVID-19: (Q1) Is it possible to contain COVID-19? (Q2) When will be the peak and the end of the epidemic? (Q3) How do the asymptomatic infec
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::23afefe566b29dd289ae00e2f88dfba6
Publikováno v:
Journal of Alloys and Compounds. 890:161796
This study determines the effect of the addition of graphene on the electrical and ferromagnetic properties of the ZnO thin films that are prepared by the sol-gel method. ZnO is a typically oxygen-deficient metal oxide and exhibits intrinsic n-type c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::97faecc80ff136bb7d5eeb1884e15537
https://doi.org/10.1016/j.jallcom.2021.161796
https://doi.org/10.1016/j.jallcom.2021.161796
In this paper, we propose a new averaging model for modeling the competitive influence of $K$ candidates among $n$ voters in an election process. For such an influence propagation model, we address the question of how many seeded voters a candidate n
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8301743474073f4df1388ea058ebf3d4
Publikováno v:
GLOBECOM Workshops
In this paper, we consider the multichannel rendezvous problem in cognitive radio networks (CRNs) where the probability that two users hopping on the same channel have a successful rendezvous is a function of channel states. The channel states are mo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0d1fa761a7d8f04a4424f05add437dd3
Publikováno v:
ICC
In this paper, we conduct centrality analysis for attributed networks. An attributed network, as a generalization of a graph, has node attributes and edge attributes that represent the ``features'' of nodes and edges. Traditionally, centrality analys
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::96fed411f6d7f23a7807f6cfd5c9aacc
https://doi.org/10.1109/icc.2018.8422245
https://doi.org/10.1109/icc.2018.8422245