Heuristic algorithm for 1D and 2D unfolding

A very simple heuristic approach to the unfolding problem will be described. An iterative algorithm starts with an empty histogram and every iteration aims to add one entry to this histogram. The entry to be added is selected according to a criteria which includes a $\chi^2$ test and a regularization. After a relatively small number of iterations (500 - 1000) the growing reconstructed distribution converges to the true distribution.