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TablePuppet: A Generic Framework for Relational Federated Learning
March 26, 2024, 4:41 a.m. | Lijie Xu, Chulin Xie, Yiran Guo, Gustavo Alonso, Bo Li, Guoliang Li, Wei Wang, Wentao Wu, Ce Zhang
cs.LG updates on arXiv.org arxiv.org
Abstract: Current federated learning (FL) approaches view decentralized training data as a single table, divided among participants either horizontally (by rows) or vertically (by columns). However, these approaches are inadequate for handling distributed relational tables across databases. This scenario requires intricate SQL operations like joins and unions to obtain the training data, which is either costly or restricted by privacy concerns. This raises the question: can we directly run FL on distributed relational tables?
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abstract arxiv cs.db cs.lg current data databases decentralized distributed federated learning framework however joins operations relational sql table tables training training data type unions view
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