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cs.LG2024
Efficient User Sequence Learning for Online Services via Compressed Graph Neural Networks
Yucheng Wu, Liyue Chen, Yu Cheng +3
Learning representations of user behavior sequences is crucial for various online services, such as online fraudulent transaction detection mechanisms. Graph Neural Networks (GNNs)…
cs.LG2023
Knowledge-inspired Subdomain Adaptation for Cross-Domain Knowledge Transfer
Liyue Chen, Linian Wang, Jinyu Xu +5
Most state-of-the-art deep domain adaptation techniques align source and target samples in a global fashion. That is, after alignment, each source sample is expected to become simi…
cs.LG2021
SHORING: Design Provable Conditional High-Order Interaction Network via Symbolic Testing
Hui Li, Xing Fu, Ruofan Wu +8
Deep learning provides a promising way to extract effective representations from raw data in an end-to-end fashion and has proven its effectiveness in various domains such as compu…