Michel Lang

Orcid: 0000-0001-9754-0393

According to our database1, Michel Lang authored at least 34 papers between 2011 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
AR-Sieve Bootstrap for the Random Forest and a simulation-based comparison with rangerts time series prediction.
CoRR, 2024

TREE: Tree Regularization for Efficient Execution.
CoRR, 2024

2023
Multi-Objective Hyperparameter Optimization in Machine Learning - An Overview.
ACM Trans. Evol. Learn. Optim., December, 2023

Fairness Audits and Debiasing Using \pkg{mlr3fairness}.
R J., March, 2023

Hyperparameter optimization: Foundations, algorithms, best practices, and open challenges.
WIREs Data. Mining. Knowl. Discov., 2023

2022
Automated Benchmark-Driven Design and Explanation of Hyperparameter Optimizers.
IEEE Trans. Evol. Comput., 2022

Multi-Objective Hyperparameter Optimization - An Overview.
CoRR, 2022

Survival Prediction and Model Selection.
Proceedings of the Machine Learning under Resource Constraints - Volume 3: Applications, 2022

2021
stabm: Stability Measures for Feature Selection.
J. Open Source Softw., 2021

mlr3pipelines - Flexible Machine Learning Pipelines in R.
J. Mach. Learn. Res., 2021

Mlr3spatiotempcv: Spatiotemporal resampling methods for machine learning in R.
CoRR, 2021

mlr3proba: an R package for machine learning in survival analysis.
Bioinform., 2021

OpenML Benchmarking Suites.
Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

Employing an Adjusted Stability Measure for Multi-criteria Model Fitting on Data Sets with Similar Features.
Proceedings of the Machine Learning, Optimization, and Data Science, 2021

2020
Benchmark for filter methods for feature selection in high-dimensional classification data.
Comput. Stat. Data Anal., 2020

mlr3proba: Machine Learning Survival Analysis in R.
CoRR, 2020

Feature Selection Methods for Cost-Constrained Classification in Random Forests.
CoRR, 2020

Cost-Constrained feature selection in binary classification: adaptations for greedy forward selection and genetic algorithms.
BMC Bioinform., 2020

Model-based optimization with concept drifts.
Proceedings of the GECCO '20: Genetic and Evolutionary Computation Conference, 2020

2019
mlr3: A modern object-oriented machine learning framework in R.
Dataset, December, 2019

mlr3: A modern object-oriented machine learning framework in R.
J. Open Source Softw., 2019

OpenML: An R package to connect to the machine learning platform OpenML.
Comput. Stat., 2019

High Dimensional Restrictive Federated Model Selection with Multi-objective Bayesian Optimization over Shifted Distributions.
Proceedings of the Intelligent Systems and Applications, 2019

2018
rsimsum: Summarise results from Monte Carlo simulation studies.
J. Open Source Softw., 2018

2017
checkmate: Fast Argument Checks for Defensive R Programming.
R J., 2017

batchtools: Tools for R to work on batch systems.
J. Open Source Softw., 2017

OpenML Benchmarking Suites and the OpenML100.
CoRR, 2017

OpenML: An R Package to Connect to the Networked Machine Learning Platform OpenML.
CoRR, 2017

A Multicriteria Approach to Find Predictive and Sparse Models with Stable Feature Selection for High-Dimensional Data.
Comput. Math. Methods Medicine, 2017

RAMBO: Resource-Aware Model-Based Optimization with Scheduling for Heterogeneous Runtimes and a Comparison with Asynchronous Model-Based Optimization.
Proceedings of the Learning and Intelligent Optimization - 11th International Conference, 2017

2016
mlr: Machine Learning in R.
J. Mach. Learn. Res., 2016

mlr Tutorial.
CoRR, 2016

Faster Model-Based Optimization Through Resource-Aware Scheduling Strategies.
Proceedings of the Learning and Intelligent Optimization - 10th International Conference, 2016

2011
Survival models with preclustered gene groups as covariates.
BMC Bioinform., 2011


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