Patent ID: 11934960
Assignee: FAIRNESS-AS-A-SERVICE, INC.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 13:
14. A method of encouraging inferential fairness of an artificial neural network, the method comprising:
computing a disparity divergence based on an approximate distribution of a non-disparity affected class of data samples and an approximate distribution of a disparity affected class of data samples;
generating a distribution-matching term based on the disparity divergence, wherein the distribution-matching term mitigates an inferential disparity between artificial neural network inferences for the non-disparity affected class of data samples and the disparity affected class of data samples during a training of an artificial neural network;
constructing a disparity-constrained loss function based on integrating the distribution-matching term with a loss function; and
training the artificial neural network using a training corpus of labeled data samples, wherein the training includes performing backpropagation using the disparity-constrained loss function.