7 citations · 10 across the 4 of their papers we have counts for
4 papers
Unifying local and global model explanations by functional decomposition of low dimensional structures
Munir Hiabu, Joseph T. Meyer, Marvin N. Wright
We consider a global representation of a regression or classification function by decomposing it into the sum of main and interaction components of arbitrary order. We propose a ne…
Optimal Convergence Rates of Deep Neural Networks in a Classification Setting
Joseph T. Meyer
We establish optimal convergence rates up to a log-factor for a class of deep neural networks in a classification setting under a restraint sometimes referred to as the Tsybakov no…
Local linear smoothing in additive models as data projection
Munir Hiabu, Enno Mammen, Joseph T. Meyer
We discuss local linear smooth backfitting for additive non-parametric models. This procedure is well known for achieving optimal convergence rates under appropriate smoothness con…
Random Planted Forest: a directly interpretable tree ensemble
Munir Hiabu, Enno Mammen, Joseph T. Meyer
We introduce a novel interpretable tree based algorithm for prediction in a regression setting. Our motivation is to estimate the unknown regression function from a functional deco…