Big Data Classification : Aspects on Many Features and Many Observations. - Claus Weihs; Daniel Horn; Bernd Bischl (ECDA, 2014)

Model-Based Multi-objective Optimization: Taxonomy, Multi-Point Proposal, Toolbox and Benchmark. - Daniel Horn; Tobias Wagner 001; Dirk Biermann; Claus Weihs; Bernd Bischl (EMO (1), 2015)

Multi-objective Selection of Algorithm Portfolios: Experimental Validation. - Daniel Horn; Karin Schork; Tobias Wagner 001 (PPSN, 2016)

Multi-objective parameter configuration of machine learning algorithms using model-based optimization. - Daniel Horn; Bernd Bischl (SSCI, 2016)

Fast model selection by limiting SVM training times. - Aydin Demircioglu; Daniel Horn; Tobias Glasmachers; Bernd Bischl; Claus Weihs (CoRR, 2016)

First Investigations on Noisy Model-Based Multi-objective Optimization. - Daniel Horn; Melanie Dagge; Xudong Sun 002; Bernd Bischl (EMO, 2017)

A First Analysis of Kernels for Kriging-Based Optimization in Hierarchical Search Spaces. - Martin Zaefferer; Daniel Horn (PPSN (2), 2018)

A comparative study on large scale kernelized support vector machines. - Daniel Horn; Aydin Demircioglu; Bernd Bischl; Tobias Glasmachers; Claus Weihs (Adv. Data Anal. Classif., 2018)

Surrogates for hierarchical search spaces: the wedge-kernel and an automated analysis. - Daniel Horn; Jörg Stork; Nils-Jannik Schüßler; Martin Zaefferer (GECCO, 2019)

Multi-objective analysis of machine learning algorithms using model-based optimization techniques - Daniel Horn (2019)

Random boosting and random^2 forests - A random tree depth injection approach. - Tobias Markus Krabel; Thi Ngoc Tien Tran; Andreas Groll; Daniel Horn; Carsten Jentsch (CoRR, 2020)

Using Sequential Statistical Tests to Improve the Performance of Random Search in hyperparameter Tuning. - Philip Buczak; Daniel Horn (CoRR, 2021)

Relationship Between Electronic Health Record Time and Ambulatory Quality of Care Metrics Among Primary Care Physicians. - Lisa S. Rotenstein; Richard Gitomer; Michael J. Healey; Daniel Horn; David Yut-Chee Ting; Stuart R. Lipsitz; Hojjat Salmasian; David W. Bates (AMIA, 2022)

RODD: Robust Outlier Detection in Data Cubes. - Lara Kuhlmann; Daniel Wilmes; Emmanuel Müller; Markus Pauly; Daniel Horn (DaWaK, 2023)

Contextual Shift Method (CSM). - Gernot Schmitz; Daniel Wilmes; Alexander Gerharz; Daniel Horn; Emmanuel Müller (DaWaK, 2023)

A Benchmark for Rule Induction in Automated Business Decisions. - Hagen Völzer; Daniel Horn; Yusik Kim; Greger Ottosson (RuleML+RR, 2024)

Adaptive Resampling with Bootstrap for Noisy Multi-Objective Optimization Problems. - Timo Budszuhn; Mark Joachim Krallmann; Daniel Horn (CoRR, 2025)

Old but Gold or New and Shiny? Comparing Tree Ensembles for Ordinal Prediction with a Classic Parametric Approach. - Philip Buczak; Daniel Horn; Markus Pauly (J. Classif., 2025)