A survey of imbalanced learning on graphs: Problems, techniques, and future directions

Z Liu, Y Li, N Chen, Q Wang, B Hooi, B He - arXiv preprint arXiv …, 2023 - arxiv.org
Graphs represent interconnected structures prevalent in a myriad of real-world scenarios.
Effective graph analytics, such as graph learning methods, enables users to gain profound …

Bert4eth: A pre-trained transformer for ethereum fraud detection

S Hu, Z Zhang, B Luo, S Lu, B He, L Liu - Proceedings of the ACM Web …, 2023 - dl.acm.org
As various forms of fraud proliferate on Ethereum, it is imperative to safeguard against these
malicious activities to protect susceptible users from being victimized. While current studies …

Sequence-based target coin prediction for cryptocurrency pump-and-dump

S Hu, Z Zhang, S Lu, B He, Z Li - … of the ACM on Management of Data, 2023 - dl.acm.org
With the proliferation of pump-and-dump schemes (P&Ds) in the cryptocurrency market, it
becomes imperative to detect such fraudulent activities in advance to alert potentially …

Lumos: Heterogeneity-aware federated graph learning over decentralized devices

Q Pan, Y Zhu, L Chu - 2023 IEEE 39th International Conference …, 2023 - ieeexplore.ieee.org
Graph neural networks (GNN) have been widely deployed in real-world networked
applications and systems due to their capability to handle graph-structured data. However …

Gift: Graph-guided feature transfer for cold-start video click-through rate prediction

Y Cao, S Hu, Y Gong, Z Li, Y Yang, Q Liu… - Proceedings of the 31st …, 2022 - dl.acm.org
Short video has witnessed rapid growth in the past few years in e-commerce platforms like
Taobao. To ensure the freshness of the content, platforms need to release a large number of …