I agree that this site is using cookies. You can find further informations
here
.
X
Login
Merkliste (
0
)
Home
About us
Home About us
Our history
Profile
Press & public relations
Friends
The library in figures
Exhibitions
Projects
Training, internships, careers
Films
Services & Information
Home Services & Information
Lending and interlibrary loans
Returns and renewals
Training and library tours
My Account
Library cards
New to the library?
Download Information
Opening hours
Learning spaces
PC, WLAN, copy, scan and print
Catalogs and collections
Home Catalogs and Collections
Rare books and manuscripts
Digital collections
Subject Areas
Our sites
Home Our sites
Central Library
Law Library (Juridicum)
BB Business and Economics (BB11)
BB Physics and Electrical Engineering
TB Engineering and Social Sciences
TB Economics and Nautical Sciences
TB Music
TB Art & Design
TB Bremerhaven
Contact the library
Home Contact the library
Staff Directory
Open access & publishing
Home Open access & publishing
Reference management: Citavi & RefWorks
Publishing documents
Open Access in Bremen
zur Desktop-Version
Toggle navigation
Merkliste
1 Ergebnisse
1
Hierarchical Reinforcement Learning Recommendation Method b..:
, In:
2023 3rd International Conference on Computer Science, Electronic Information Engineering and Intelligent Control Technology (CEI)
,
Yan, Bowen
;
Yan, Mengwei
;
Li, Wenxin
. - p. 386-389 , 2023
Link:
https://doi.org/10.1109/CEI60616.2023.10528035
RT T1 <cTitle>2023 3rd International Conference on Computer Science, Electronic Information Engineering and Intelligent Control Technology (CEI)</cTitle>: T1 <Title>Hierarchical Reinforcement Learning Recommendation Method based on Deep Interest Networks</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10528035&Exemplar=1&LAN=DE A1 Yan, Bowen A1 Yan, Mengwei A1 Li, Wenxin A1 Jia, Yanan YR 2023 K1 Computer science K1 Adaptation models K1 Electronic learning K1 Correlation K1 Reinforcement learning K1 Vectors K1 Task analysis K1 Disease Deep Interest Network K1 Hierarchical Reinforcement Learning K1 MOOC SP 386 OP 389 LK http://dx.doi.org/https://doi.org/10.1109/CEI60616.2023.10528035 DO https://doi.org/10.1109/CEI60616.2023.10528035 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)
