Learning to Pivot with Adversarial Networks

Understand

Several techniques for domain adaptation have been proposed to account for differences in the distribution of the data used for training and testing.

• The majority of this work focuses on a binary domain label.
• Similar problems occur in a scientific context where there may be a continuous family of plausible data generation processes associated to the presence of systematic uncertainties.
• Robust inference is possible if it is based on a pivot -- a quantity whose distribution does not depend on the unknown values of the nuisance parameters that parametrize this family of data generation processes.