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1 Ergebnisse
1
Supervised pretraining through contrastive categorical posi..:
, In:
Proceedings of the 13th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics
,
Wanyan, Tingyi
;
Lin, Mingquan
;
Klang, Eyal
... - p. 1-9 , 2022
Link:
https://dl.acm.org/doi/10.1145/3535508.3545541
RT T1 <cTitle>Proceedings of the 13th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics</cTitle>: T1 <Title>Supervised pretraining through contrastive categorical positive samplings to improve COVID-19 mortality prediction</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3545541&Exemplar=1&LAN=DE A1 Wanyan, Tingyi A1 Lin, Mingquan A1 Klang, Eyal A1 Menon, Kartikeya M. A1 Gulamali, Faris F. A1 Azad, Ariful A1 Zhang, Yiye A1 Ding, Ying A1 Wang, Zhangyang A1 Wang, Fei A1 Glicksberg, Benjamin A1 Peng, Yifan PB ACM YR 2022 K1 intra-class variance K1 mortality prediction K1 pre-training K1 self-supervised learning K1 sub-phenotype K1 supervised contrastive learning K1 Theory of computation K1 Theory and algorithms for application domains K1 Machine learning theory K1 Models of learning SP 1 OP 9 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3535508.3545541 DO https://dl.acm.org/doi/10.1145/3535508.3545541 SF ELIB - SuUB Bremen
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