Personalized Machine Learning System

摘要

Machine learning may be personalized to individual users of computing devices, and can be used to increase machine learning prediction accuracy and speed, and/or reduce memory footprint. Personalizing machine learning can include hosting, by a computing device, a consensus machine learning model and collecting information, locally by the computing device, associated with an application executed by the client device. Personalizing machine learning can also include modifying the consensus machine learning model accessible by the application based, at least in part, on the information collected locally by the client device. Modifying the consensus machine learning model can generate a personalized machine learning model. Personalizing machine learning can also include transmitting the personalized machine learning model to a server that updates the consensus machine learning model.

主权项

1. A method comprising:
hosting, by a client device, a consensus machine learning model; collecting information, locally by the client device, associated with an application executed by the client device; and modifying the consensus machine learning model accessible by the application based, at least in part, on the information collected locally by the client device, wherein modifying the consensus machine learning model generates a personalized machine learning model; transmitting the personalized machine learning model to a server; and receiving a global machine learning model from the server, wherein the global machine learning model is based, at least in part, on i) the personalized machine learning model transmitted to the server and ii) an aggregation of a plurality of other personalized machine learning models transmitted from a plurality of other client devices to the server.