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Ming Hu

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Book Open access Aug 2026

FedKDD/FedMAS 2026: The 2026 International Joint Workshop on Federated Learning for Multi-agent Systems and Data Mining

Multi-agent systems (MAS) are enabling increasingly complex, collaborative applications in autonomous driving, smart logistics, robotic coordination, and distributed sensing. Their effectiveness depends on collective intelligence emerging from multiple distributed agents, each operating with partial information and oft...

Hao-Zhao Wang, Zhuangdi Zhu, Zheng Xu et al. · 0 citations
2025

Rising from Ashes: Generalized Federated Learning via Dynamic Parameter Reset

A novel FL framework is presented, FedPhoenix, that stochastically re-sets partial parameters in each round to destroy some features of the global model, guiding FL training to learn multiple generalized features for inference rather than specific overfitting features.

Jia-Hao Wu, Ming Hu, Yanxin Yang et al. · 1 citation

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