14 citations · 14 across the 2 of their papers we have counts for
3 papers
cs.LG2020
Wide Boosting
Michael T. Horrell
Gradient Boosting (GB) is a popular methodology used to solve prediction problems by minimizing a differentiable loss function, . GB performs very well on tabular machine learni…
stat.ME2015
Half-Spectral Space-Time Covariance Models
Michael T. Horrell, Michael L. Stein
We develop two new classes of space-time Gaussian process models by specifying covariance functions using what we call a half-spectral representation. The half-spectral representat…
stat.ML2013★ 14 cited
Nonparametric Reduced Rank Regression
Rina Foygel, Michael Horrell, Mathias Drton +1
We propose an approach to multivariate nonparametric regression that generalizes reduced rank regression for linear models. An additive model is estimated for each dimension of a $…