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A new parameter choice rule for inverse problems is introduced. Thisparameter choice rule was developed for total variation regularization inelectron tomography and might in general be useful for $L^1$ regularization ofinverse problems with high levels of noise in the data.

A new principle for choosing regularization parameter in certain inverse problems