Trend-Aware Proactive Caching via Tensor Train Decomposition: A Bayesian Viewpoint

Reference : Trend-Aware Proactive Caching via Tensor Train Decomposition: A Bayesian Viewpoint


	Document type :	Scientific journals : Article
	Discipline(s) :	Engineering, computing & technology : Electrical & electronics engineering
	To cite this reference:	http://hdl.handle.net/10993/48195

Title :	Trend-Aware Proactive Caching via Tensor Train Decomposition: A Bayesian Viewpoint
Language :	English
Author, co-author :	Mehrizi Rahmat Abadi, Sajad [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom >]
	X. Vu, Thang [> >]
	Chatzinotas, Symeon [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom >]
	Ottersten, Björn [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Publication date :	22-Apr-2021
Journal title :	IEEE Open Journal of the Communications Society
Publisher :	Luxembourg
Issue/season :	4369
Peer reviewed :	Yes
e-ISSN :	2644-125X
City :	New York
Country :	NY
Permalink :	http://hdl.handle.net/10993/48195
	also: http://hdl.handle.net/10993/50262
FnR project :	FnR ; FNR11826975 > Sajad Mehrizi > LISTEN > Online Learning For Edge-caching In Hybrid Satellite-terrestrial Networks > 01/09/2017 > 31/08/2021 > 2017

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