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Sep 2026

Robust Bidding Strategies under Censored Feedback for Auction-Based Federated Learning.

Auction-based Federated Learning (AFL) provides a principled framework for incentivizing self-interested data owners (DOs) to participate in collaborative learning initiated by data consumers (DCs) through market mechanisms. A central challenge in AFL is to determine how a budget-constrained DC should bid for data-use...

Xiao-Li Tang, Ying-Peng Tang, Zhuang Qi et al. · 0 citations
#federated learning Open access Oct 2026

LLM‐Powered Data Synthesis on Blockchain for Fusion Isomerism Learning in Heterogeneous Federated Systems

Severe data starvation, architectural heterogeneity and Byzantine vulnerabilities fundamentally impede the deployment of robust multiclass classification models in decentralised edge environments. To address these intertwined challenges, we propose fusion isomerism learning (FusionIL) , a secure and domain‐agnost...

Zhi-Hao Hao, Long-Bing Cao, Han Yu et al. · 0 citations

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