Customizable federated learning

An apparatus, comprising:

• one or more network interfaces;
• a processor coupled to the one or more network interfaces and configured to execute one or more processes;
• and
• a memory configured to store a process that is executable by the processor, the process when executed configured to:
• identify a first dataset and a second dataset available to a particular node of a federated learning system, wherein the first dataset comprises features that are common to all nodes of the federated learning system, and wherein the second dataset comprises features that are common only to a subset of nodes of the federated learning system;
• configure the particular node to train a first model using the first dataset;
• cause 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;
• configure the particular node to train a second model using the second dataset.

A tangible, non-transitory, computer-readable medium storing program instructions that cause a controller for a federated learning system to execute a process comprising:

• identifying, by the controller, a first dataset and a second dataset available to a particular node of the federated learning system, wherein the first dataset comprises features that are common to all nodes of the federated learning system, and wherein the second dataset comprises features that are common only to a subset of nodes of the federated learning system;
• configuring, by the controller, the particular node to train a first model using the first dataset;
• causing, by the controller, 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;
• configuring, by the controller, the particular node to train a second model using the second dataset.