Carolin Benjamins

According to our database, Carolin Benjamins authored at least 11 papers between 2021 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of three.

2023

POLTER: Policy Trajectory Ensemble Regularization for Unsupervised Reinforcement Learning.

Frederik Schubert, Carolin Benjamins, Sebastian Döhler, Bodo Rosenhahn, Marius Lindauer

Trans. Mach. Learn. Res., 2023

Towards Self-Adjusting Weighted Expected Improvement for Bayesian Optimization.

Carolin Benjamins, Elena Raponi, Anja Jankovic, Carola Doerr, Marius Lindauer

Proceedings of the Companion Proceedings of the Conference on Genetic and Evolutionary Computation, 2023

AutoRL Hyperparameter Landscapes.

Aditya Mohan, Carolin Benjamins, Konrad Wienecke, Alexander Dockhorn, Marius Lindauer

Proceedings of the International Conference on Automated Machine Learning, 2023

Self-Adjusting Weighted Expected Improvement for Bayesian Optimization.

Carolin Benjamins, Elena Raponi, Anja Jankovic, Carola Doerr, Marius Lindauer

Proceedings of the International Conference on Automated Machine Learning, 2023

2022

SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization.

Marius Lindauer, Katharina Eggensperger, Matthias Feurer, André Biedenkapp, Difan Deng, Carolin Benjamins, Tim Ruhkopf, René Sass, Frank Hutter

J. Mach. Learn. Res., 2022

Hyperparameters in Contextual RL are Highly Situational.

Theresa Eimer, Carolin Benjamins, Marius Lindauer

CoRR, 2022

Towards Automated Design of Bayesian Optimization via Exploratory Landscape Analysis.

Carolin Benjamins, Anja Jankovic, Elena Raponi, Koen van der Blom, Marius Lindauer, Carola Doerr

CoRR, 2022

PI is back! Switching Acquisition Functions in Bayesian Optimization.

Carolin Benjamins, Elena Raponi, Anja Jankovic, Koen van der Blom, Maria Laura Santoni, Marius Lindauer, Carola Doerr

CoRR, 2022

Contextualize Me - The Case for Context in Reinforcement Learning.

Carolin Benjamins, Theresa Eimer, Frederik Schubert, Aditya Mohan, André Biedenkapp, Bodo Rosenhahn, Frank Hutter, Marius Lindauer

CoRR, 2022

2021

CARL: A Benchmark for Contextual and Adaptive Reinforcement Learning.

Carolin Benjamins, Theresa Eimer, Frederik Schubert, André Biedenkapp, Bodo Rosenhahn, Frank Hutter, Marius Lindauer

CoRR, 2021

SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization.

Marius Lindauer, Katharina Eggensperger, Matthias Feurer, André Biedenkapp, Difan Deng, Carolin Benjamins, René Sass, Frank Hutter

CoRR, 2021