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Ziquan Fang

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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. · 0 citations