3 papers
cs.LG2025
Behavioral Anomaly Detection in Distributed Systems via Federated Contrastive Learning
Renzi Meng, Heyi Wang, Yumeng Sun +3
This paper addresses the increasingly prominent problem of anomaly detection in distributed systems. It proposes a detection method based on federated contrastive learning. The goa…
cs.LG2025
Graph Neural Network-Based Collaborative Perception for Adaptive Scheduling in Distributed Systems
Wenxuan Zhu, Qiyuan Wu, Tengda Tang +3
This paper addresses the limitations of multi-node perception and delayed scheduling response in distributed systems by proposing a GNN-based multi-node collaborative perception me…
cs.LG2025
Deep Probabilistic Modeling of User Behavior for Anomaly Detection via Mixture Density Networks
Lu Dai, Wenxuan Zhu, Xuehui Quan +3
To improve the identification of potential anomaly patterns in complex user behavior, this paper proposes an anomaly detection method based on a deep mixture density network. The m…