Jakob Richter

Orcid: 0000-0003-4481-5554

According to our database1, Jakob Richter authored at least 16 papers between 2016 and 2023.

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

Timeline

Legend:

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In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

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

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

A Probabilistic Neural Twin for Treatment Planning in Peripheral Pulmonary Artery Stenosis.
CoRR, 2023

In silico high-resolution whole lung model to predict the locally delivered dose of inhaled drugs.
CoRR, 2023

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
MODES: model-based optimization on distributed embedded systems.
Mach. Learn., 2021

2020
Extending model-based optimization with resource-aware parallelization and for dynamic optimization problems
PhD thesis, 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.
J. Open Source Softw., 2019

Model-based optimization of subgroup weights for survival analysis.
Bioinform., 2019

2018
Performance evaluation and hyperparameter tuning of statistical and machine-learning models using spatial data.
CoRR, 2018

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


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