Book
Open access
Aug 2026
FedTT: A Federated Spatio-Temporal Learning Framework for Cross-City Traffic Knowledge Transfer
This work proposes FedTT, a federated spatio-temporal learning framework for cross-city traffic knowledge transfer that consistently outperforms 18 state-of-the-art baselines, achieving improved prediction accuracy while maintaining strong empirical resistance to attacks.
Zhihao Zeng, Ziquan Fang, Yuting Huang et al.
· Proceedings of the 32nd ACM... · 0 citations