Microsoft Corporation
Neural network architecture for attention based efficient model adaptation

Last updated:

Abstract:

A neural network architecture for attention-based efficient model adaptation is disclosed. A method includes accessing an input vector, the input vector comprising a numeric representation of an input to a neural network. The method includes providing the input vector to the neural network comprising a plurality of ordered layers, wherein each layer in at least a subset of the plurality of ordered layers is coupled with an adaptation module, wherein the adaptation module receives a same input value as a coupled layer for the adaptation module, and wherein an output value of the adaptation module is pointwise multiplied with an output value of the coupled layer to generate a next layer input value. The method includes generating an output of the neural network based on an output of a last one of the plurality of ordered layers in the neural network.

Status:
Grant
Type:

Utility

Filling date:

18 Dec 2018

Issue date:

14 Jun 2022