Generating new samples from data sets can mitigate extra expensive operations, increased invasive procedures, and mitigate privacy issues. These novel samples that are statistically robust can be used as a temporary and intermediate replacement when privacy is a concern. This method can enable better data sharing practices without problems relating to identification issues or biases that are flaws for an adversarial attack.

翻译：从数据集中产生新的样本可以减少超昂贵的操作,增加入侵程序,减少隐私问题。 这些在统计上稳健的新样本可以在隐私问题引起关注时用作临时和中间替代。 这种方法可以促进更好的数据共享做法,而不会出现与识别问题或对立攻击缺陷的偏见有关的问题。