Daniel Schalk

According to our database, Daniel Schalk authored at least 8 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Privacy-preserving and lossless distributed estimation of high-dimensional generalized additive mixed models.

Daniel Schalk, Bernd Bischl, David Rügamer

Stat. Comput., February, 2024

2023

Accelerated Componentwise Gradient Boosting Using Efficient Data Representation and Momentum-Based Optimization.

Daniel Schalk, Bernd Bischl, David Rügamer

J. Comput. Graph. Stat., April, 2023

dsBinVal: Conducting distributed ROC analysis using DataSHIELD.

Daniel Schalk, Verena S. Hoffmann, Bernd Bischl, Ulrich Mansmann

J. Open Source Softw., March, 2023

Multimodal Deep Learning.

Cem Akkus, Luyang Chu, Vladana Djakovic, Steffen Jauch-Walser, Philipp Koch, Giacomo Loss, Christopher Marquardt, Marco Moldovan, Nadja Sauter, Maximilian Schneider, Rickmer Schulte, Karol Urbanczyk, Jann Goschenhofer, Christian Heumann, Rasmus Hvingelby, Daniel Schalk, Matthias Aßenmacher

CoRR, 2023

2022

Distributed non-disclosive validation of predictive models by a modified ROC-GLM.

Daniel Schalk, Verena S. Hoffmann, Bernd Bischl, Ulrich Mansmann

CoRR, 2022

2021

Automatic Componentwise Boosting: An Interpretable AutoML System.

Stefan Coors, Daniel Schalk, Bernd Bischl, David Rügamer

CoRR, 2021

2019

Component-Wise Boosting of Targets for Multi-Output Prediction.

Quay Au, Daniel Schalk, Giuseppe Casalicchio, Ramona Schödel, Clemens Stachl, Bernd Bischl

CoRR, 2019

2018

compboost: Modular Framework for Component-Wise Boosting.

Daniel Schalk, Janek Thomas, Bernd Bischl

J. Open Source Softw., 2018