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

Claim 0:
1. A computer-implemented method for mitigating disparities of inferential outputs of a machine learning model, the method comprising:
generating an indiscernibility constraint based on a distribution divergence metric value computed between a distribution associated with a non-disparity affected class of data samples and a distribution associated with a disparity affected class of data samples, wherein the indiscernibility constraint mitigates a machine learning-based inferential disparity between the non-disparity affected class of data samples and the disparity affected class of data samples during a training of a target machine learning model;
configuring a disparity-mitigating loss function based on augmenting a gradient descent algorithm with the indiscernibility constraint; and
training the target machine learning model using a training corpus of labeled data samples, wherein the training includes performing backpropagation using the disparity-mitigating loss function.