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
Geometric deep reinforcement learning for dynamic DAG sched..:
, In:
2020 IEEE Symposium Series on Computational Intelligence (SSCI)
,
Grinsztajn, Nathan
;
Beaumont, Olivier
;
Jeannot, Emmanuel
. - p. 258-265 , 2020
Link:
https://doi.org/10.1109/SSCI47803.2020.9308278
RT T1
2020 IEEE Symposium Series on Computational Intelligence (SSCI)
: T1
Geometric deep reinforcement learning for dynamic DAG scheduling
UL https://suche.suub.uni-bremen.de/peid=ieee-9308278&Exemplar=1&LAN=DE A1 Grinsztajn, Nathan A1 Beaumont, Olivier A1 Jeannot, Emmanuel A1 Preux, Philippe YR 2020 K1 Task analysis K1 Kernel K1 Reinforcement learning K1 Heuristic algorithms K1 Runtime K1 Dynamic scheduling K1 Optimization K1 scheduling K1 task graph K1 DAG K1 high performance computing K1 combinatorial optimization SP 258 OP 265 LK http://dx.doi.org/https://doi.org/10.1109/SSCI47803.2020.9308278 DO https://doi.org/10.1109/SSCI47803.2020.9308278 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)