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A federated machine learning approach to detect internation..:

, In: Proceedings of the 37th ACM/SIGAPP Symposium on Applied Computing,

Ferreira, Luís ; Silva, Leopoldo ; Pinho, Diana... - p. 1432-1439 , 2022

Link: https://dl.acm.org/doi/10.1145/3477314.3507322

RT 
T1 <cTitle>Proceedings of the 37th ACM/SIGAPP Symposium on Applied Computing</cTitle>: T1 <Title>A federated machine learning approach to detect international revenue share fraud on the 5G edge</Title>

UL https://suche.suub.uni-bremen.de/peid=acm-3507322&Exemplar=1&LAN=DE
				
A1 Ferreira, Luís
A1 Silva, Leopoldo
A1 Pinho, Diana
A1 Morais, Francisco
A1 Martins, Carlos Manuel
A1 Pires, Pedro Miguel
A1 Fidalgo, Pedro
A1 Rodrigues, Helena
A1 Cortez, Paulo
A1 Pilastri, André
PB ACM
YR 2022
K1 5G networks
K1 edge computing
K1 federated learning
K1 machine learning
K1 multi-access edge computing
K1 Computer systems organization
K1 Architectures
K1 Distributed architectures
K1 Computing methodologies
K1 Machine learning
K1 Machine learning approaches
K1 Neural networks
K1 Learning paradigms
K1 Supervised learning
K1 Supervised learning by classification
SP 1432
OP 1439
LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3477314.3507322
DO https://dl.acm.org/doi/10.1145/3477314.3507322
SF ELIB - SuUB Bremen

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