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 factors
are useful for a wide range of problems: removing potential biases in
prediction problems, controlling the effects of covariates, and disentangling
meaningful factors of variation. Unfortunately, learning representations that
exhibit invariance to arbitrary nuisance factors yet remain