Daniel Moyer, Shuyang Gao, Rob Brekelmans, Greg Ver Steeg, Aram Galstyan
TL;DR无需对抗训练，使用信息论优化能够直接获得可控转换的公平表示和生成建模的最新性能
Abstract
Representations of data that are invariant to changes in specified nuisance factors are useful for a wide range of problems: removing potential bias in prediction problems, controlling the effects of known confounders, and disentangling meaningful factors of variation. Unfortunately, learning representations that exhibit invariance to arbitrary nuisance fact