2 papers
stat.ML2024
AR-Sieve Bootstrap for the Random Forest and a simulation-based comparison with rangerts time series prediction
Cabrel Teguemne Fokam, Carsten Jentsch, Michel Lang +1
The Random Forest (RF) algorithm can be applied to a broad spectrum of problems, including time series prediction. However, neither the classical IID (Independent and Identically d…
cs.LG2024
TREE: Tree Regularization for Efficient Execution
Lena Schmid, Daniel Biebert, Christian Hakert +4
The rise of machine learning methods on heavily resource constrained devices requires not only the choice of a suitable model architecture for the target platform, but also the opt…