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
GradFilt: Class-wise Targeted Data Reconstruction from Grad..:
, In:
Companion Proceedings of the ACM Web Conference 2024
,
Zhang, Rui
;
Guo, Song
;
Li, Ping
- p. 698-701 , 2024
Link:
https://dl.acm.org/doi/10.1145/3589335.3651514
RT T1 <cTitle>Companion Proceedings of the ACM Web Conference 2024</cTitle>: T1 <Title>GradFilt: Class-wise Targeted Data Reconstruction from Gradients in Federated Learning</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3651514&Exemplar=1&LAN=DE A1 Zhang, Rui A1 Guo, Song A1 Li, Ping PB ACM YR 2024 K1 federated learning K1 gradient inversion K1 privacy leakage K1 Security and privacy K1 Systems security K1 Distributed systems security K1 Computing methodologies K1 Machine learning SP 698 OP 701 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3589335.3651514 DO https://dl.acm.org/doi/10.1145/3589335.3651514 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)
