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
Fix Fairness, Don't Ruin Accuracy: Performance Aware Fairne..:
, In:
Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering
,
Nguyen, Giang
;
Biswas, Sumon
;
Rajan, Hridesh
- p. 502-514 , 2023
Link:
https://dl.acm.org/doi/10.1145/3611643.3616257
RT T1
Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering
: T1
Fix Fairness, Don't Ruin Accuracy: Performance Aware Fairness Repair using AutoML
UL https://suche.suub.uni-bremen.de/peid=acm-3616257&Exemplar=1&LAN=DE A1 Nguyen, Giang A1 Biswas, Sumon A1 Rajan, Hridesh PB ACM YR 2023 K1 Software fairness K1 automated machine learning K1 bias mitigation K1 fairness-accuracy trade-off K1 machine learning software K1 Software and its engineering K1 Search-based software engineering K1 Computing methodologies K1 Machine learning SP 502 OP 514 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3611643.3616257 DO https://dl.acm.org/doi/10.1145/3611643.3616257 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)