Scab disease of firethorn at selected localities in Slovakia

  • Juhásová G
  • Ivanová H
  • Adamčíková K
  • et al.
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Abstract

We introduce a family of adaptive estimators on graphs, based on penalizing the $\ell_1$ norm of discrete graph differences. This generalizes the idea of trend filtering [Kim et al. (2009), Tibshirani (2014)], used for univariate nonparametric regression, to graphs. Analogous to the univariate case, graph trend filtering exhibits a level of local adaptivity unmatched by the usual $\ell_2$-based graph smoothers. It is also defined by a convex minimization problem that is readily solved (e.g., by fast ADMM or Newton algorithms). We demonstrate the merits of graph trend filtering through examples and theory.

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Juhásová, G., Ivanová, H., Adamčíková, K., Kobza, M., & Čerevková, A. (2004). Scab disease of firethorn at selected localities in Slovakia. Plant Protection Science, 40(2), 42–48. https://doi.org/10.17221/461-pps

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