International Business Machines Corporation

University of Michigan

Debarghya Mukherjee

Sohini Upadhyay

Mikhail Yurochkin

Yuekai Sun

Amanda Ruth Garcia Bower

Seyed Hamid Eftekhari

Alexander Vargo

Fan Zhang

Obtain a first data set, a second data set, and a machine learning model. Construct a sensitive subspace of the first data set that defines a fair metric for distance among elements of the first data set. Fairly train the machine learning model on the first data set using a distributionally robust optimization approach based on the fair metric. Produce an individually fair set of labels by applying the fairly trained machine learning model to the second data set. Allocate a resource according to the individually fair set of labels.

Training individually fair machine learning algorithms via distributionally robust optimization

Growing community of inventors

Ann Arbor, MI, United States of America

Debarghya Mukherjee