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
A New Cardinality Estimation Method Based on Graph Neural N..:
, In:
Proceedings of the 2023 International Conference on Frontiers of Artificial Intelligence and Machine Learning
,
Song, Yuan Feng
;
Li, Xiao Dong
;
Zhang, Dan Ni
.. - p. 153-159 , 2023
Link:
https://dl.acm.org/doi/10.1145/3616901.3616936
RT T1
Proceedings of the 2023 International Conference on Frontiers of Artificial Intelligence and Machine Learning
: T1
A New Cardinality Estimation Method Based on Graph Neural Networks
UL https://suche.suub.uni-bremen.de/peid=acm-3616936&Exemplar=1&LAN=DE A1 Song, Yuan Feng A1 Li, Xiao Dong A1 Zhang, Dan Ni A1 Fan, Shu Huan A1 He, Dong Sheng PB ACM YR 2023 K1 Cardinality estimation K1 Graph neural network K1 Query optimization K1 Computing methodologies K1 Machine learning K1 Machine learning approaches K1 Neural networks SP 153 OP 159 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3616901.3616936 DO https://dl.acm.org/doi/10.1145/3616901.3616936 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)