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：针对高斯序列模型的经典去噪过程，探讨了两种稳健化策略。首先，采用Hodges与Lehmann（1952）提出的受限贝叶斯方法，以降低对初始先验分布设定的敏感性。其次，探索了高斯噪声假设的替代方案。在这两种情形下，Huber（1964）与Mallows（1978）的提议均发挥了关键作用。