论文标题
比在灌木丛中敲打钉子更好：用单个投影去除受保护的属性
Better Hit the Nail on the Head than Beat around the Bush: Removing Protected Attributes with a Single Projection
论文作者
论文摘要
偏见消除和最近的探测研究试图从嵌入空间中删除特定信息。在这里，请删除尽可能多的目标信息，同时保留存在的任何其他信息，这一点很重要。 INLP是一种流行的方法，可通过迭代零空间预测删除特定信息。但是，多次迭代会增加对目标以外的信息受到负面影响的风险。我们介绍了两种找到单个目标投影的方法：平均投影（MP，更有效）和Tukey中值投影（TMP，具有理论保证）。我们在MP和INLP之间的比较表明，（1）一个MP投影根据目标去除线性可分离性，并且（2）MP对整个空间的影响较小。进一步的分析表明，在MP之后应用随机预测会导致对嵌入空间的总体影响与INLP的多个投影相同。因此，应用一个靶向（MP）投影在方法上比应用多个（INLP）投影更清洁。
Bias elimination and recent probing studies attempt to remove specific information from embedding spaces. Here it is important to remove as much of the target information as possible, while preserving any other information present. INLP is a popular recent method which removes specific information through iterative nullspace projections. Multiple iterations, however, increase the risk that information other than the target is negatively affected. We introduce two methods that find a single targeted projection: Mean Projection (MP, more efficient) and Tukey Median Projection (TMP, with theoretical guarantees). Our comparison between MP and INLP shows that (1) one MP projection removes linear separability based on the target and (2) MP has less impact on the overall space. Further analysis shows that applying random projections after MP leads to the same overall effects on the embedding space as the multiple projections of INLP. Applying one targeted (MP) projection hence is methodologically cleaner than applying multiple (INLP) projections that introduce random effects.
