= Graph total variation denoising
{title2=$\widehat\theta=\arg\min_\theta\{n^{-1}\|y-\theta\|_2^2+\lambda\|D\theta\|_1\}$}
Graph total variation denoising is a <penalized least-squares estimator> for noisy vertex signals on a <graph>. The squared loss is strictly <convex>, so the fitted signal is unique. Its <basic inequality for a penalized least-squares estimator> separates a noise inner product from the change in penalty. The <incidence pseudoinverse decomposition> controls the nonconstant noise through the geometry of the <graph>.
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