Shan Chang

Fed-CAD: Federated Learning with Correlation-aware Adaptive Local Differential Privacy

2024

Federated Learning (FL) enables multiple participants to collaboratively train a globally shared model without the need of explicit data sharing. However, prior research indicates that local model updates released during the federated training may also …

Learning Triple-View Representation Discrepancy for Multivariate Time Series Anomaly Detection with Multi-Scale Patching

2024

Multivariate time series anomaly detection is a longstanding but crucial technology, holding significant potential for system security and stability. Prior studies focus on designing sophisticated architectures, integrating advanced modules (e.g., CNN, LSTM, and Transformer), and …