This paper mainly studies how to select reasonable stepsizes (regularization parameters) in Lanczos’ generalized derivatives. Four posterior selection strategies, in which two strategies need to know the noise level while the other two do not, are proposed with the convergence estimates of regularization solutions (Lanczos’ generalized derivatives). Numerical experiments show that the last three posterior selection strategies, i.e. Posterior Selection Strategies II–IV, are feasible for Lanczos’ generalized derivatives.

中文翻译：

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Lanczos广义导数正则化参数的后验选择策略

本文主要研究如何在Lanczos的广义导数中选择合理的步长（正则化参数）。提出了四种后验选择策略，其中两种策略需要知道噪声水平，而另两种策略则不需要，但是需要对正则化解进行收敛估计（Lanczos的广义导数）。数值实验表明，最后三种后验选择策略，即后验选择策略II–IV，对于Lanczos的广义导数是可行的。