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EvoFed: Leveraging Evolutionary Strategies for Communication-Efficient Federated Learning
This global fitness vector is then disseminated back to the nodes, each of which applies the same update to be synchronized to the global model.
Locally Supervised Learning with Periodic Global Guidance
Locally supervised learning aims to train a neural network based on a local estimation of the global loss function at each decoupled module of the network.
Accelerating Federated Split Learning via Local-Loss-Based Training
Federated learning (FL) operates based on model exchanges between the server and the clients, and suffers from significant communication as well as client-side computation burden.
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