FedGTA: Topology-Aware Averaging for Federated Graph Learning
Xunkai Li,
Zhengyu Wu,
Wentao Zhang
et al.
Abstract:Federated Graph Learning (FGL) is a distributed machine learning paradigm that enables collaborative training on large-scale subgraphs across multiple local systems. Existing FGL studies fall into two categories: (i) FGL Optimization, which improves multi-client training in existing machine learning models; (ii) FGL Model, which enhances performance with complex local models and multi-client interactions. However, most FGL optimization strategies are designed specifically for the computer vision domain and ign… Show more
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