0


概率推理与差异隐私

Probabilistic Inference and Differential Privacy
课程网址: http://videolectures.net/nips2010_mcsherry_pid/  
主讲教师: Frank McSherry
开课单位: 微软公司
开课时间: 2011-03-25
课程语种: 英语
中文简介:
我们识别并研究概率推理和差异隐私之间的紧密联系,后者是最近的隐私定义,其仅允许通过噪声测量间接观察数据。以前关于差异隐私的研究主要集中在设计测量过程,其输出可能是有用的。我们考虑将概率推理应用于测量和测量过程以得出数据集及其模型参数的后验分布的可能性。我们发现概率推理可以提高准确性,整合多个观察结果,测量不确定性,甚至可以提供未直接测量的数量的后验分布。
课程简介: We identify and investigate a strong connection between probabilistic inference and differential privacy, the latter being a recent privacy definition that permits only indirect observation of data through noisy measurement. Previous research on differential privacy has focused on designing measurement processes whose output is likely to be useful on its own. We consider the potential of applying probabilistic inference to the measurements and measurement process to derive posterior distributions over the data sets and model parameters thereof. We find that probabilistic inference can improve accuracy, integrate multiple observations, measure uncertainty, and even provide posterior distributions over quantities that were not directly measured.
关 键 词: 概率推理; 差异隐私; 噪声测量
课程来源: 视频讲座网
最后编审: 2020-04-27:chenxin
阅读次数: 61