Tikhonov regularization is a cornerstone technique in solving inverse problems with applications in countless scienti¿c ¿elds. Richard Huber discusses a multi-parameter Tikhonov approach for systems of inverse problems in order to take advantage of their speci¿c structure. Such an approach allows to choose the regularization weights of each subproblem individually with respect to the corresponding noise levels and degrees of ill-posedness.