English(EN) From Euclidean to Graph-Structured Data: A Survey of Collaborative Learning

调查将协作学习从欧几里得数据映射到图结构数据

作者 PulseAugur 编辑部 · [2 个来源] · 2026-09-02 13:49

本次调查论文探讨了协作学习从传统欧几里得数据到更复杂的图结构数据的演变。通过考察联邦学习和去中心化学习等方法，解决了中心化机器学习的可扩展性和隐私问题等局限性。该论文对图分布场景进行了分类，并提出了图上学习的标准框架，强调了这一新兴领域中开放的挑战和未来的研究方向。 AI

影响本次调查整合了图结构数据的协作学习研究，可能指导未来在隐私保护和可扩展机器学习应用方面的发展。

排序理由该集群包含一篇在 arXiv 上发表的调查论文，详细介绍了机器学习方面的研究。

AI 生成摘要 · Google Gemini · 来自 2 个来源。我们如何撰写摘要 →

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Newsworthiness bucket: Research; 该集群包含一篇在 arXiv 上发表的调查论文，详细介绍了机器学习方面的研究。
Source corroboration: 2 independent sources; Multiple independent publishers reporting the same story raises confidence that it's real and newsworthy.
Topics: paper, other; Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance: High; Clearly on-topic for AI-industry coverage.
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arXiv cs.LG TIER_1 English(EN) · R\'emi Bourgerie, \v{S}ar\=unas Girdzijauskas, Viktoria Fodor · 2026-09-04 04:00

从欧几里得空间到图结构数据：协同学习调查

arXiv:2609.02984v1 Announce Type: new Abstract: The conventional approach to machine learning, that is, collecting data, training models, and performing inference in a single location, faces fundamental limitations, including scalability and privacy, that restrict its applicabili…
arXiv cs.MA (Multiagent) TIER_1 English(EN) · Viktoria Fodor · 2026-09-02 13:49

从欧几里得空间到图结构数据：协同学习的调查

The conventional approach to machine learning, that is, collecting data, training models, and performing inference in a single location, faces fundamental limitations, including scalability and privacy, that restrict its applicability. To address these challenges, recent research…