MSc. Theresa Eimer
Leibniz Universität Hannover
Institut für Informationsverarbeitung
Appelstr. 9A
30167 Hannover
Germany
phone: +49 511 762-5322
fax: +49 511 762-5333
office location: room 1331

I moved to the Institute of AI on July 1st 2022. My new website is here.

Theresa Eimer studied Computer Science at the Albert-Ludwigs Universität Freiburg and recieved her Master's degree in 2019. Her thesis "Improved Meta-Learning for Algorithm Control through Self-Paced Learning" showed the benefits of automatically generated learning curricula for Dynamic Algorithm Configuration. Since 2020 she is working towards a PhD as a doctoral researcher at the Institut für Informationsverarbeitung.

Her main research interest is AutoML, more specifically Dynamic Algorithm Configuration which aims to control algorithm hyperparameters on the fly in order to improve the algorithm's performance. A focus here is on the use of Transfer and Meta-Learning techniques for Reinforcement Learning in order to make training more efficient and enable knowledge transfer between instances and problems.

Show recent publications only
  • Conference Contributions
    • Theresa Eimer, Carolin Benjamins, Marius Lindauer
      Hyperparameters in Contextual RL are Highly Situational
      NeurIPS 2021 Workshop on Ecological Theory of Reinforcement Learning, December 2021
    • Carolin Benjamins, Theresa Eimer, Frederik Schubert, André Biedenkapp, Bodo Rosenhahn, Frank Hutter, Marius Lindauer
      CARL: A Benchmark for Contextual and Adaptive Reinforcement Learning
      NeurIPS 2021 Workshop on Ecological Theory of Reinforcement Learning, December 2021
    • Theresa Eimer, André Biedenkapp, Maximilian Reimer, Steven Adriaensen, Frank Hutter, Marius Lindauer
      DACBench: A Benchmark Library for Dynamic Algorithm Configuration
      Proceedings of the international joint conference on artificial intelligence (IJCAI), August 2021
    • Theresa Eimer, Andre Biedenkapp, Frank Hutter, Marius Lindauer
      Self-Paced Context Evaluation for Contextual Reinforcement Learning
      Proceedings of the international conference on machine learning (ICML), July 2021
    • Frederik Schubert, Theresa Eimer, Bodo Rosenhahn, Marius Lindauer
      Towards Automatic Risk Adaption in Distributional Reinforcement Learning
      Reinforcement Learning for Real Life (RL4RealLife) Workshop in the 38th International Conference on Machine Learning (ICML), July 2021
    • Theresa Eimer, Andre Biedenkapp, Frank Hutter, Marius Lindauer
      Towards Self-Paced Context Evaluations for Contextual Reinforcement Learning
      Workshop on Inductive Biases, Invariances and Generalization in Reinforcement Learning (BIG@ICML'20), July 2020
    • Andre Biedenkapp, H. Furkan Bozkurt, Theresa Eimer, Frank Hutter, Marius Lindauer
      Algorithm Control: Foundation of a New Meta-Algorithmic Framework
      Proceedings of the European Conference on Artificial Intelligence (ECAI), 2020
  • Journals
    • Jack Parker-Holder, Raghu Rajan, Xingyou Song, André Biedenkapp, Yingjie Miao, Theresa Eimer, Baohe Zhang, Vu Nguyen, Roberto Calandra, Aleksandra Faust, Frank Hutter, Marius Lindauer
      Automated Reinforcement Learning (AutoRL): A Survey and Open Problems
      Journal of Artificial Intelligence Research (JAIR), 2022
  • Technical Report
    • Steven Adriaensen, André Biedenkapp, Gresa Shala, Noor Awad, Theresa Eimer, Marius Lindauer, Frank Hutter
      Automated Dynamic Algorithm Configuration
      ArXiv, May 2022
    • Carolin Benjamins, Theresa Eimer, Frederik Schubert, Aditya Mohan, André Biedenkapp, Bodo Rosenhahn, Frank Hutter, Marius Lindauer
      Contextualize Me - The Case for Context in Reinforcement Learning
      ArXiv Preprint, February 2022
    • Frederik Schubert, Theresa Eimer, Bodo Rosenhahn, Marius Lindauer
      Automatic Risk Adaptation in Distributional Reinforcement Learning
      Arxiv Preprint, June 2021