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ESCM2 : Entire Space Counterfactual Multi-Task Model for..:

, In: Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval,

Wang, Hao ; Chang, Tai-Wei ; Liu, Tianqiao... - p. 363-372 , 2022

Link: https://dl.acm.org/doi/10.1145/3477495.3531972

RT 
T1 <cTitle>Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval</cTitle>: T1 <Title>ESCM2				: Entire Space Counterfactual Multi-Task Model for Post-Click Conversion Rate Estimation</Title>

UL https://suche.suub.uni-bremen.de/peid=acm-3531972&Exemplar=1&LAN=DE
				
A1 Wang, Hao
A1 Chang, Tai-Wei
A1 Liu, Tianqiao
A1 Huang, Jianmin
A1 Chen, Zhichao
A1 Yu, Chao
A1 Li, Ruopeng
A1 Chu, Wei
PB ACM
YR 2022
K1 entire space multi-task learning
K1 post-click conversion rate estimation
K1 recommender system
K1 selection bias
K1 Information systems
K1 Information retrieval
K1 Retrieval tasks and goals
K1 Recommender systems
K1 Computing methodologies
K1 Artificial intelligence
K1 Knowledge representation and reasoning
K1 Causal reasoning and diagnostics
K1 Machine learning
K1 Learning paradigms
K1 Multi-task learning
SP 363
OP 372
LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3477495.3531972
DO https://dl.acm.org/doi/10.1145/3477495.3531972
SF ELIB - SuUB Bremen

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