AI RESEARCH
Personalized Collaborative Learning with Affinity-Based Variance Reduction
arXiv CS.LG
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ArXi:2510.16232v3 Announce Type: replace-cross Multi-agent learning faces a fundamental tension: leveraging distributed collaboration without sacrificing the personalization needed for diverse agents. This tension intensifies when aiming for full personalization while adapting to unknown heterogeneity levels -- gaining collaborative speedup when agents are similar, without performance degradation when they are different.