3 citations · 7 across the 11 of their papers we have counts for
4 papers · 1 filter
agtboost: Adaptive and Automatic Gradient Tree Boosting Computations
Berent Ånund Strømnes Lunde, Tore Selland Kleppe
agtboost is an R package implementing fast gradient tree boosting computations in a manner similar to other established frameworks such as xgboost and LightGBM, but with significan…
An information criterion for automatic gradient tree boosting
Berent Ånund Strømnes Lunde, Tore Selland Kleppe, Hans Julius Skaug
An information theoretic approach to learning the complexity of classification and regression trees and the number of trees in gradient tree boosting is proposed. The optimism (tes…
Connecting the Dots: Numerical Randomized Hamiltonian Monte Carlo with State-Dependent Event Rates
Tore Selland Kleppe
Numerical Generalized Randomized Hamiltonian Monte Carlo is introduced, as a robust, easy to use and computationally fast alternative to conventional Markov chain Monte Carlo metho…
Estimating the Competitive Storage Model with Stochastic Trends in Commodity Prices
Kjartan Kloster Osmundsen, Tore Selland Kleppe, Roman Liesenfeld +1
We propose a state-space model (SSM) for commodity prices that combines the competitive storage model with a stochastic trend. This approach fits into the economic rationality of s…