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Sponsored Design Multi-Agent AI Systems Using MCP and A2A: Engineer your own Pyt Design Multi-Agent AI Systems Using MCP and A2A: Engineer your own Pyt

Author

Xiaolong Xu

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Conference Open access Sep 2026

BAMFair: Barycenter Aligned Mediation for Fairness Across Multiple Sensitive Attributes

Achieving fairness in machine learning models while maintaining high accuracy is an important but complex task, especially when handling multiple sensitive attributes. Traditional fairness methods often struggle to eliminate bias within subgroups divided by sensitive attributes. Several key challenges have been identif...

Heng-Yu Yue, Fan Wang, Wei-Ming Liu et al. · 0 citations
2025

A Fair Federated Learning Method for Handling Client Participation Probability Inconsistencies in Heterogeneous Environments

This work proposes PHP-FL, a novel model-heterogeneous FL method that explicitly addresses scenarios with varying client participation probabilities to enhance both model accuracy and performance fairness, and introduces a Dual-End Aligned ensemble Learning (DEAL) module.

Siyuan Wu, Yongzhe Jia, Haolong Xiang et al. · 1 citation · ⚡1

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