no code implementations • COLING 2022 • Li Gao, Lingyun Song, Jie Liu, Bolin Chen, Xuequn Shang
However, little attention is paid to the issues of both authenticity of the relationships and topology imbalance in the structure of NPG, which trick existing methods and thus lead to incorrect prediction results.
no code implementations • 14 Mar 2024 • Jie Liu, Xuequn Shang, Xiaolin Han, Wentao Zhang, Hongzhi Yin
Then STRIPE incorporates separate spatial and temporal memory networks, which capture and store prototypes of normal patterns, thereby preserving the uniqueness of spatial and temporal normality.
no code implementations • 25 Dec 2023 • Yupei Zhang, Yuxin Li, Yifei Wang, Shuangshuang Wei, Yunan Xu, Xuequn Shang
To this end, this study proposes a distributed grade prediction model, dubbed FecMap, by exploiting the federated learning (FL) framework that preserves the private data of local clients and communicates with others through a global generalized model.
no code implementations • 15 Dec 2023 • Xiran Qu, Xuequn Shang, Yupei Zhang
This paper studies the problem of CPRP, concept prerequisite relation prediction, which is a fundamental task in using AI for education.
no code implementations • 28 Jul 2023 • Jie Liu, Mengting He, Xuequn Shang, Jieming Shi, Bin Cui, Hongzhi Yin
By swapping the context embeddings between nodes and edges and measuring the agreement in the embedding space, we enable the mutual detection of node and edge anomalies.
no code implementations • 28 Apr 2023 • Jie Liu, Mengting He, Guangtao Wang, Nguyen Quoc Viet Hung, Xuequn Shang, Hongzhi Yin
minority classes to balance the label and topology distribution.
no code implementations • 7 Sep 2018 • Hansheng Xue, Jiajie Peng, Xuequn Shang
Network Embedding, aiming to learn non-linear and low-dimensional feature representation based on network topology, has been proved to be helpful on tasks of network analysis, especially node classification.