Accurate and efficient inference in multi-device environments

A computer-implemented method for network communications by a client device, comprising:

• transmitting, to a host device, a data set associated with the client device;
• receiving a version of a task-specific model trained based on at least a feature set extracted from the transmitted data set;
• receiving an input for processing;
• generating an inference based on the received input and the received version of the task-specific model;
• and
• performing one or more actions based on the inference.

A host device comprising:

• memory having executable instructions stored thereon;
• and
• one or more processors configured to execute the executable instructions in order to cause the host device to:
• extract a feature set from a data set associated with a client device using a client-device-specific feature extractor, wherein the feature set comprises a subset of features in a common feature space;
• train a task-specific model based on the extracted feature set and one or more other feature sets associated with other client devices, wherein the other feature sets associated with the other client devices comprise one or more subsets of features in the common feature space;
• and
• deploy, to each respective client device of a plurality of client devices, a respective version of the task-specific model.

A client device comprising:

• memory having executable instructions stored thereon;
• and
• one or more processors configured to execute the executable instructions in order to cause the client device to:
• transmit, to a host device, a data set associated with the client device;
• receive a version of a task-specific model trained based on at least a feature set extracted from the transmitted data set;
• receive an input for processing;
• generate an inference based on the received input and the received version of the task-specific model;
• and
• perform one or more actions based on the inference.