Apple Inc.

Dewey H Lee

Daniel R Kurz

Qian Wang

Thomas Gebauer

Muhammad Ahmed Riaz

The present disclosure describes techniques for training a neural network such that the trained network can be implemented to perform a utility task (e.g., a classification task) while inhibiting performance of a secondary task (e.g., a privacy-violating task). In some embodiments, the techniques include training a neural network using a first loss associated with a first task and a second loss associated with a second task different from the first task. In some embodiments, this includes performing a first training operation associated with the first loss, and performing a second training operation associated with the second loss, wherein the second training operation includes providing, to the neural network, a plurality of input items associated with the second task.

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Sunnyvale, CA, United States of America

Dewey H Lee