arXiv stat.ML
· Papers
Statistical inverse learning and $ell^1$-regularization
arXiv:2607.07468v1 Announce Type: new Abstract: We study the recovery of sparse functions from finite, noisy, and indirect observations in the framework of statistical inverse learning. The unknown is modeled as an element of $ell^1$, and observations are generated through a possibly nonlinear forward operator $A:ell