App usage models with privacy protection

A server comprising:

• a memory comprising instructions;
• and
• one or more computer processors, wherein the instructions, when executed by the one or more computer processors, cause the server to perform operations comprising:
• receiving model information from a plurality of client devices, the model information being for a model obtained at each client device by training a machine-learning program with app usage data obtained at the client device;
• generating synthetic data generated using the models from the plurality of client devices;
• training a machine-learning program using the synthetic data to obtain a global model, the global model receiving as input information about at least one recent command entered on the app and generating an output comprising at least one prediction for the next command expected to be received by the app, wherein the training is based on features comprising a command identifier (ID), a timestamp, a context of use in the app, information about a user interacting with the app, and information about the client device;
• and
• transmitting information of the global model to a first client device from the plurality of client devices, wherein the global model executing on the first client device generates the prediction for the next command expected, wherein the app executing on the first client device provides at least one command option in an app user interface comprising the next command expected.

A tangible machine-readable storage medium including instructions that, when executed by a machine, cause the machine to perform operations comprising:

• receiving, at a server, synthetic data generated at a plurality of client devices using models executing at the plurality of client devices, each model being obtained at each client device by training a machine-learning program with app usage data obtained at the client device;
• training a machine-learning program using the synthetic data to obtain a global model, the global model receiving as input information about at least one recent command entered on the app and generating an output comprising at least one prediction for the next command expected to be received by the app;
• and
• transmitting information of the global model to a first client device from the plurality of client devices, wherein the global model executing on the first client device generates the prediction for the next command expected, wherein the app executing on the first client device provides at least one command option in an app user interface comprising the next command expected.