Patent ID: 11915120
Assignee: GOOGLE LLC
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 0:
1. A computer-implemented method for training a machine-learned model for flexible-multi-task learning, the method comprising:
obtaining a test input;
selecting a particular task from a plurality of tasks; and
training the machine-learned model for the particular task, wherein training the machine-learned model for the particular task comprises:
obtaining a routing matrix associated with the particular task, the routing matrix comprising a plurality of values configured to activate one or more components of a layer of the machine-learned model based on the particular task, wherein a respective value of the routing matrix is obtained by:
sampling, using a respective probability value associated with a respective component and the particular task, the respective value of the routing matrix;

processing the test input using the machine-learned model to generate an output;
training the activated one or more components based at least in part on the output; and
training, using an approximation, the machine-learned model to obtain the routing matrix.