48 citations · 74 across the 13 of their papers we have counts for
3 papers · 1 filter
Accelerated Componentwise Gradient Boosting using Efficient Data Representation and Momentum-based Optimization
Daniel Schalk, Bernd Bischl, David Rügamer
Componentwise boosting (CWB), also known as model-based boosting, is a variant of gradient boosting that builds on additive models as base learners to ensure interpretability. CWB…
Neural Mixture Distributional Regression
David Rügamer, Florian Pfisterer, Bernd Bischl
We present neural mixture distributional regression (NMDR), a holistic framework to estimate complex finite mixtures of distributional regressions defined by flexible additive pred…
mlr3proba: An R Package for Machine Learning in Survival Analysis
Raphael Sonabend, Franz J. Király, Andreas Bender +2
As machine learning has become increasingly popular over the last few decades, so too has the number of machine learning interfaces for implementing these models. Whilst many R lib…