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1 Ergebnisse
1
TreeXGNN: can gradient-boosted decision trees help boost he..:
, In:
ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
,
Hong, Ming-Yi
;
Chang, Shih-Yen
;
Hsu, Hao-Wei
... - p. 1-5 , 2023
Link:
https://doi.org/10.1109/ICASSP49357.2023.10096251
RT T1 <cTitle>ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)</cTitle>: T1 <Title>TreeXGNN: can gradient-boosted decision trees help boost heterogeneous graph neural networks?</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10096251&Exemplar=1&LAN=DE A1 Hong, Ming-Yi A1 Chang, Shih-Yen A1 Hsu, Hao-Wei A1 Huang, Yi-Hsiang A1 Wang, Chih-Yu A1 Lin, Che YR 2023 SN 2379-190X K1 Training K1 Knowledge engineering K1 Deep learning K1 Signal processing K1 Feature extraction K1 Graph neural networks K1 Decision trees K1 Heterogeneous information network K1 graph neural network K1 gradient-boosted decision trees K1 node classification K1 feature extraction SP 1 OP 5 LK http://dx.doi.org/https://doi.org/10.1109/ICASSP49357.2023.10096251 DO https://doi.org/10.1109/ICASSP49357.2023.10096251 SF ELIB - SuUB Bremen
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