2 citations · 3 across the 3 of their papers we have counts for
3 papers
stat.CO2021
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…
stat.ML2021★ 1 cited
Automatic Componentwise Boosting: An Interpretable AutoML System
Stefan Coors, Daniel Schalk, Bernd Bischl +1
In practice, machine learning (ML) workflows require various different steps, from data preprocessing, missing value imputation, model selection, to model tuning as well as model e…
stat.ML2019★ 2 cited
Component-Wise Boosting of Targets for Multi-Output Prediction
Quay Au, Daniel Schalk, Giuseppe Casalicchio +3
Multi-output prediction deals with the prediction of several targets of possibly diverse types. One way to address this problem is the so called problem transformation method. This…