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FedAds: A Benchmark for Privacy-Preserving CVR Estimation w..:

, In: Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval,

Wei, Penghui ; Dou, Hongjian ; Liu, Shaoguo... - p. 3037-3046 , 2023

Link: https://dl.acm.org/doi/10.1145/3539618.3591909

RT 
T1 <cTitle>Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval</cTitle>: T1 <Title>FedAds: A Benchmark for Privacy-Preserving CVR Estimation with Vertical Federated Learning</Title>

UL https://suche.suub.uni-bremen.de/peid=acm-3591909&Exemplar=1&LAN=DE
				
A1 Wei, Penghui
A1 Dou, Hongjian
A1 Liu, Shaoguo
A1 Tang, Rongjun
A1 Liu, Li
A1 Wang, Liang
A1 Zheng, Bo
PB ACM
YR 2023
K1 ad ranking
K1 deep generative model
K1 vertical federated learning
K1 Information systems
K1 Information retrieval
K1 Users and interactive retrieval
K1 Personalization
K1 World Wide Web
K1 Online advertising
K1 Computing methodologies
K1 Machine learning
K1 Machine learning approaches
K1 Neural networks
K1 Security and privacy
K1 Human and societal aspects of security and privacy
K1 Privacy protections
K1 Software and application security
K1 Web application security
SP 3037
OP 3046
LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3539618.3591909
DO https://dl.acm.org/doi/10.1145/3539618.3591909
SF ELIB - SuUB Bremen

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