1 code implementation • 19 Oct 2017 • Gilles Blanchard, Marc Hoffmann, Markus Reiß
We consider truncated SVD (or spectral cut-off, projection) estimators for a prototypical statistical inverse problem in dimension $D$.
Statistics Theory Statistics Theory 65J20, 62G07
1 code implementation • 24 Jun 2016 • Gilles Blanchard, Marc Hoffmann, Markus Reiß
For linear inverse problems $Y=\mathsf{A}\mu+\xi$, it is classical to recover the unknown signal $\mu$ by iterative regularisation methods $(\widehat \mu^{(m)}, m=0, 1,\ldots)$ and halt at a data-dependent iteration $\tau$ using some stopping rule, typically based on a discrepancy principle, so that the weak (or prediction) squared-error $\|\mathsf{A}(\widehat \mu^{(\tau)}-\mu)\|^2$ is controlled.
Statistics Theory Statistics Theory 65J20, 62G07
