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From Euclidean to Graph-Structured Data: A Survey of Collaborative Learning

arXiv · AI, language, vision and robotics · article · Sep 2, 2026 · UTC

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 has explored collaborative learning approaches, including federated learning and decentralized learning, where individual agents perform training and inference locally, with limited collaboration. Most collaborative learning research focuses on Euclidean data with regular, grid-like structure (e.g., images, text). How

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