Publications

Publications are listed in reversed chronological order.

2024

  1. Structure in Deep Reinforcement Learning: A survey and open problems
    Aditya MohanAmy Zhang, and Marius Lindauer
    Journal of Artificial Intelligence Research (JAIR), 2024

2023

  1. AutoRL Hyperparameter Landscapes
    Aditya MohanCarolin Benjamins, Konrad Wienecke, Alexander Dockhorn, and Marius Lindauer
    Proceedings of the Second International Conference on Automated Machine Learning (AutoML), 2023
  2. Contextualize Me - The Case for Context in Reinforcement Learning
    Carolin BenjaminsTheresa EimerF. SchubertAditya Mohan, Andre Biedenkapp, Bodo RosenhahnFrank Hutter, and Marius Lindauer
    Transactions on Machine Learning Research (TMLR), 2023
  3. Learning Activation Functions for Sparse Neural Networks
    Mohammad LoniAditya Mohan, Mehdi Asadi, and Marius Lindauer
    Proceedings of the Second International Conference on Automated Machine Learning (AutoML), 2023
  4. MASIF: Meta-learned Algorithm Selection using Implicit Fidelity Information
    Transactions on Machine Learning Research (TMLR), 2023
  5. AutoML in the Age of Large Language Models: Current Challenges, Future Opportunities and Risks
    Alexander TornedeDifan DengTheresa Eimer, Joseph Giovanelli, Aditya MohanTim Ruhkopf, Sarah Segel, Daphne Theodorakopoulos, Tanja Tornede, Henning Wachsmuth, and Marius Lindauer
    arXiv preprint arXiv:2306.08107, 2023

2022

  1. Towards Meta-learned Algorithm Selection using Implicit Fidelity Information
    Aditya MohanTim Ruhkopf, and Marius Lindauer
    ICML 2022 Workshop Adaptive Experimental Design and Active Learning in the Real World (ReALML), 2022