Two strategies are explored for robustifying classical denoising procedures for the Gaussian sequence model. First, the Hodges and Lehmann (1952) restricted Bayes approach is used to reduce sensitivity to the specification of the initial prior distribution. Second, alternatives to the Gaussian noise assumption are explored. In both cases proposals of Huber (1964) and Mallows (1978) play a crucial role.

翻译：本文探讨了两种用于稳健化高斯序列模型中经典去噪过程的策略。首先，采用Hodges和Lehmann（1952）提出的限制贝叶斯方法，以降低对初始先验分布设定的敏感性。其次，研究了高斯噪声假设的替代方案。在这两种情况下，Huber（1964）和Mallows（1978）提出的方法都发挥了关键作用。