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GLASU: A Communication-Efficient Algorithm for Federated Learning with Vertically Distributed Graph Data
[article]
2023
arXiv
pre-print
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For graph-structured data, graph neural networks (GNNs) are competitive machine learning models, but a naive implementation in the VFL setting causes a significant communication overhead. ...
Vertical federated learning (VFL) is a distributed learning paradigm, where computing clients collectively train a model based on the partial features of the same set of samples they possess. ...
Conclusion We have presented a flexible model splitting approach for VFL with vertically distributed graph data and proposed a communication-efficient algorithm, GLASU, to train the resulting GNN. ...
arXiv:2303.09531v1
fatcat:4z2quugatzdxlfs6hbwmlkbhf4
Interconnection Network Analysis and Design An Adaptable Parallel Search of Knovvledge Bases with Beam Search Survey of the MAP Project Realibility Prediction of Parsys Hypercube Architecture Komunikacija človek-računalnik v regulacijski tehniki Nevronske mreže Rekurzivni postopek testiranja večnivoiskesa komunikacijskega
unpublished
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Acknowledgments I vvish to thank ali my coUeagues at the Department,for the Study of Intelligent Systems at OZIR for many hours of inspiring discussion and a fevv years of Al research, especially Ivan ...
I vvould certainly like to see stronger biological support for this vievv, vvhich I nevertheless consider intuitive enough to be convincing. ...
The mapping is reguired when the communication graph of a parallel algorithm differs from the interconnection architecture of the physical parallel machine. ...
fatcat:zp63d6tt4nehrm7jnafyshuynq