FGAD: Self-boosted Knowledge Distillation for An Effective Federated Graph Anomaly Detection Framework

no code implementations • 20 Feb 2024 • Jinyu Cai, Yunhe Zhang, Zhoumin Lu, Wenzhong Guo, See-Kiong Ng

Although federated learning offers a promising solution, the prevalent non-IID problems and high communication costs present significant challenges, particularly pronounced in collaborations with graph data distributed among different participants.

Federated Learning Graph Anomaly Detection +1

Hyper-Laplacian Regularized Concept Factorization in Low-rank Tensor Space for Multi-view Clustering

no code implementations • 22 Apr 2023 • Zixiao Yu, Lele Fu, Zhiling Cai, Zhoumin Lu

To well cope with the issues, we propose a hyper-Laplacian regularized concept factorization (HLRCF) in low-rank tensor space for multi-view clustering.

Clustering Multi-view Subspace Clustering