no code implementations • 30 Dec 2022 • Addison J. Hu, Alden Green, Ryan J. Tibshirani
We study an estimator that forms the Voronoi diagram of the design points, and then solves an optimization problem that regularizes according to a certain discrete notion of total variation (TV): the sum of weighted absolute differences of parameters $\theta_i,\theta_j$ (which estimate the function values $f_0(x_i), f_0(x_j)$) at all neighboring cells $i, j$ in the Voronoi diagram.
no code implementations • 29 Dec 2021 • Veeranjaneyulu Sadhanala, Yu-Xiang Wang, Addison J. Hu, Ryan J. Tibshirani
We study a multivariate version of trend filtering, called Kronecker trend filtering or KTF, for the case in which the design points form a lattice in $d$ dimensions.
