Controlling Classifier Bias with Moment Decomposition: A Method to Enhance Searches for Resonances

Moment Decorrelation (MoDe) is a tool that can enforce decorrelation between some nuisance parameter (or protected attribute in ML fairness lingo) and the response of some model with gradient-based optimization (a neural network for example.) It can force trained models to have the same response across different values of the protected attribute but it can also go beyond simple decorrelation. For example, MoDe can constrain the response function to be linear or quadratic in the protected attribute.