An alternative view of the deconvolution problem

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Methodology for non‐parametric deconvolution when the error distribution is unknown (2016, methodology): “As in Delaigle et al. (2008), this suggests taking h to be an estimator of the two-stage plug-in bandwidth of Delaigle and Gijbels (2002, 2004), which is usually employed when computing”
Density estimation with heteroscedastic error (2008, background): “…advantageous – in some cases (ordinary smooth), the averaged errors become smoother and thus imply a slower rate of convergence – in finite samples, the variance reduction induced by the averaging process can lead to significant improvement of performance of the estimator; see Delaigle (2008).”