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AdaGCL : Adaptive Subgraph Contrastive Learning to Gener..:

, In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management,

Wang, Yili ; Zhou, Kaixiong ; Miao, Rui.. - p. 2046-2055 , 2022

Link: https://dl.acm.org/doi/10.1145/3511808.3557228

RT 
T1 <cTitle>Proceedings of the 31st ACM International Conference on Information & Knowledge Management</cTitle>: T1 <Title>AdaGCL				: Adaptive Subgraph Contrastive Learning to Generalize Large-scale Graph Training</Title>

UL https://suche.suub.uni-bremen.de/peid=acm-3557228&Exemplar=1&LAN=DE
				
A1 Wang, Yili
A1 Zhou, Kaixiong
A1 Miao, Rui
A1 Liu, Ninghao
A1 Wang, Xin
PB ACM
YR 2022
K1 contrastive learning
K1 data augmentation
K1 graph neural networks
K1 large-scale graphs
K1 Computing methodologies
K1 Machine learning
K1 Learning paradigms
K1 Supervised learning
K1 Supervised learning by classification
K1 Machine learning approaches
K1 Learning latent representations
K1 Computer systems organization
K1 Architectures
K1 Other architectures
K1 Neural networks
K1 Information systems
K1 Information systems applications
K1 Data mining
SP 2046
OP 2055
LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3511808.3557228
DO https://dl.acm.org/doi/10.1145/3511808.3557228
SF ELIB - SuUB Bremen

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