Survival models with preclustered gene groups as covariates. - Kai Kammers; Michel Lang; Jan G. Hengstler; Marcus Schmidt; Jörg Rahnenführer (BMC Bioinform., 2011)

Faster Model-Based Optimization Through Resource-Aware Scheduling Strategies. - Jakob Richter; Helena Kotthaus; Bernd Bischl; Peter Marwedel; Jörg Rahnenführer; Michel Lang (LION, 2016)

mlr Tutorial. - Julia Schiffner; Bernd Bischl; Michel Lang; Jakob Richter; Zachary M. Jones; Philipp Probst; Florian Pfisterer; Mason Gallo; Dominik Kirchhoff; Tobias Kühn; Janek Thomas; Lars Kotthoff (CoRR, 2016)

mlr: Machine Learning in R. - Bernd Bischl; Michel Lang; Lars Kotthoff; Julia Schiffner; Jakob Richter; Erich Studerus; Giuseppe Casalicchio; Zachary M. Jones (J. Mach. Learn. Res., 2016)

RAMBO: Resource-Aware Model-Based Optimization with Scheduling for Heterogeneous Runtimes and a Comparison with Asynchronous Model-Based Optimization. - Helena Kotthaus; Jakob Richter; Andreas Lang 002; Janek Thomas; Bernd Bischl; Peter Marwedel; Jörg Rahnenführer; Michel Lang (LION, 2017)

A Multicriteria Approach to Find Predictive and Sparse Models with Stable Feature Selection for High-Dimensional Data. - Andrea Bommert; Jörg Rahnenführer; Michel Lang (Comput. Math. Methods Medicine, 2017)

OpenML: An R Package to Connect to the Networked Machine Learning Platform OpenML. - Giuseppe Casalicchio; Jakob Bossek; Michel Lang; Dominik Kirchhoff; Pascal Kerschke; Benjamin Hofner; Heidi Seibold; Joaquin Vanschoren; Bernd Bischl (CoRR, 2017)

OpenML Benchmarking Suites and the OpenML100. - Bernd Bischl; Giuseppe Casalicchio; Matthias Feurer; Frank Hutter; Michel Lang; Rafael Gomes Mantovani; Jan N. van Rijn; Joaquin Vanschoren (CoRR, 2017)

batchtools: Tools for R to work on batch systems. - Michel Lang; Bernd Bischl; Dirk Surmann (J. Open Source Softw., 2017)

checkmate: Fast Argument Checks for Defensive R Programming. - Michel Lang (R J., 2017)

rsimsum: Summarise results from Monte Carlo simulation studies. - Alessandro Gasparini; Michel Lang (J. Open Source Softw., 2018)

High Dimensional Restrictive Federated Model Selection with Multi-objective Bayesian Optimization over Shifted Distributions. - Xudong Sun 002; Andrea Bommert; Florian Pfisterer; Jörg Rahnenführer; Michel Lang; Bernd Bischl (IntelliSys (1), 2019)

OpenML: An R package to connect to the machine learning platform OpenML. - Giuseppe Casalicchio; Jakob Bossek; Michel Lang; Dominik Kirchhoff; Pascal Kerschke; Benjamin Hofner; Heidi Seibold; Joaquin Vanschoren; Bernd Bischl (Comput. Stat., 2019)

mlr3: A modern object-oriented machine learning framework in R. - Michel Lang; Martin Binder; Jakob Richter; Patrick Schratz; Florian Pfisterer; Stefan Coors; Quay Au; Giuseppe Casalicchio; Lars Kotthoff; Bernd Bischl (J. Open Source Softw., 2019)

mlr3: A modern object-oriented machine learning framework in R. - Michel Lang; Martin Binder; Jakob Richter; Patrick Schratz; Florian Pfisterer; Stefan Coors; Quay Au; Giuseppe Casalicchio; Lars Kotthoff; Bernd Bischl (Zenodo, 2019)

Model-based optimization with concept drifts. - Jakob Richter; Junjie Shi; Jian-Jia Chen; Jörg Rahnenführer; Michel Lang (GECCO, 2020)

Cost-Constrained feature selection in binary classification: adaptations for greedy forward selection and genetic algorithms. - Rudolf Jagdhuber; Michel Lang; Arnulf Stenzl; Jochen Neuhaus; Jörg Rahnenführer (BMC Bioinform., 2020)

Feature Selection Methods for Cost-Constrained Classification in Random Forests. - Rudolf Jagdhuber; Michel Lang; Jörg Rahnenführer (CoRR, 2020)

mlr3proba: Machine Learning Survival Analysis in R. - Raphael Sonabend; Franz J. Király; Andreas Bender 001; Bernd Bischl; Michel Lang (CoRR, 2020)

Benchmark for filter methods for feature selection in high-dimensional classification data. - Andrea Bommert; Xudong Sun 002; Bernd Bischl; Jörg Rahnenführer; Michel Lang (Comput. Stat. Data Anal., 2020)

Employing an Adjusted Stability Measure for Multi-criteria Model Fitting on Data Sets with Similar Features. - Andrea Bommert; Jörg Rahnenführer; Michel Lang (LOD, 2021)

OpenML Benchmarking Suites. - Bernd Bischl; Giuseppe Casalicchio; Matthias Feurer; Pieter Gijsbers; Frank Hutter; Michel Lang; Rafael Gomes Mantovani; Jan N. van Rijn; Joaquin Vanschoren (NeurIPS Datasets and Benchmarks, 2021)

mlr3proba: an R package for machine learning in survival analysis. - Raphael Sonabend; Franz J. Király; Andreas Bender 001; Bernd Bischl; Michel Lang (Bioinform., 2021)

Mlr3spatiotempcv: Spatiotemporal resampling methods for machine learning in R. - Patrick Schratz; Marc Becker; Michel Lang; Alexander Brenning (CoRR, 2021)

mlr3pipelines - Flexible Machine Learning Pipelines in R. - Martin Binder; Florian Pfisterer; Michel Lang; Lennart Schneider; Lars Kotthoff; Bernd Bischl (J. Mach. Learn. Res., 2021)

stabm: Stability Measures for Feature Selection. - Andrea Bommert; Michel Lang (J. Open Source Softw., 2021)

Survival Prediction and Model Selection. - Jörg Rahnenführer; Michel Lang; Jakob Richter (Mach. Learn. under Resour. Constraints Vol. 3 (3), 2022)

Multi-Objective Hyperparameter Optimization - An Overview. - Florian Karl; Tobias Pielok; Julia Moosbauer; Florian Pfisterer; Stefan Coors; Martin Binder; Lennart Schneider; Janek Thomas; Jakob Richter; Michel Lang; Eduardo C. Garrido-Merchán; Jürgen Branke; et al. (CoRR, 2022)

Automated Benchmark-Driven Design and Explanation of Hyperparameter Optimizers. - Julia Moosbauer; Martin Binder; Lennart Schneider; Florian Pfisterer; Marc Becker; Michel Lang; Lars Kotthoff; Bernd Bischl (IEEE Trans. Evol. Comput., 2022)

Hyperparameter optimization: Foundations, algorithms, best practices, and open challenges. - Bernd Bischl; Martin Binder; Michel Lang; Tobias Pielok; Jakob Richter; Stefan Coors; Janek Thomas; Theresa Ullmann; Marc Becker; Anne-Laure Boulesteix; Difan Deng; Marius Lindauer (WIREs Data. Mining. Knowl. Discov., 2023)

Fairness Audits and Debiasing Using pkg{mlr3fairness}. - Florian Pfisterer; Siyi Wei; Sebastian J. Vollmer; Michel Lang; Bernd Bischl (R J., 2023)

Multi-Objective Hyperparameter Optimization in Machine Learning - An Overview. - Florian Karl; Tobias Pielok; Julia Moosbauer; Florian Pfisterer; Stefan Coors; Martin Binder; Lennart Schneider; Janek Thomas; Jakob Richter; Michel Lang; Eduardo C. Garrido-Merchán; Jürgen Branke; et al. (ACM Trans. Evol. Learn. Optim., 2023)

TREE: Tree Regularization for Efficient Execution. - Lena Schmid; Daniel Biebert; Christian Hakert; Kuan-Hsun Chen; Michel Lang; Markus Pauly; Jian-Jia Chen (CoRR, 2024)

AR-Sieve Bootstrap for the Random Forest and a simulation-based comparison with rangerts time series prediction. - Cabrel Teguemne Fokam; Carsten Jentsch; Michel Lang; Markus Pauly (CoRR, 2024)

mlr3spatiotempcv: Spatiotemporal Resampling Methods for Machine Learning in R. - Patrick Schratz; Marc Becker; Michel Lang; Alexander Brenning (J. Stat. Softw., 2024)