Invention Publication

CUSTOMIZABLE FEDERATED LEARNING
Abstract:
In one embodiment, a controller for a federated learning system identifies a first dataset and a second dataset available to a particular node of the federated learning system. The first dataset comprises features that are common to all nodes of the federated learning system. The second dataset comprises features that are common only to a subset of nodes of the federated learning system. The controller configures the particular node to train a first model using the first dataset. The controller causes formation of a global model in the federated learning system that aggregates the first model from the particular node with models from all other nodes of the federated learning system. The controller configures the particular node to train a second model using the second dataset.
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