AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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FedIGL: Federated Invariant Graph Learning for Non-IID Graphs
This work proposes a FedIGL framework based on invariant learning, which effectively disrupts spurious correlations and further mines the invariant factors across different distributions, and proposes a novel Bi-Gradient Regularization strategy that introduces gradient constraints to guide the model in identifying clie...