Regularization parameter
= Regularization parameter
{title2=$\alpha$}
A regularization parameter controls the tradeoff between approximation bias and data-noise amplification in an <inverse problem>. For <early stopping of Landweber iteration> with fixed step $\tau$, the convention $\alpha=1/(\tau n)$ associates a smaller parameter with more iterations.