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2020

  • Speck, D. and Biedenkapp, A. and Hutter, F. and Mattmüller, R. and Lindauer, M. (arXiv)(bib)
    Learning Heuristic Selection with Dynamic Algorithm Configuration
    In: Workshop on Bridging the Gap Between AI Planning and Reinforcement Learning (PRL@ICAPS'20)
    (Code)(Project Page)
  • Franke, J. KH and Köhler, G. and Biedenkapp, A. and Hutter, F. (arXiv)(bib)
    Sample-Efficient Automated Deep Reinforcement Learning
    In: arXiv:2009.01555 [cs.LG] (2020)
  • Shala, G. and Biedenkapp, A. and Awad, N. and Adriaensen, S. and Lindauer, M. and Hutter, F. (pdf)(poster)(bib)
    Learning Step-Size Adaptation in CMA-ES
    In: Proceedings of the Sixteenth International Conference on Parallel Problem Solving from Nature (PPSN'20)
    (Video presentation)(Code)(Project Page)
  • Eimer, T. and Biedenkapp, A. and Hutter, F. and Lindauer, M. (pdf)(bib)
    Towards Self-Paced Context Evaluations for Contextual Reinforcement Learning
    In: Workshop on Inductive Biases, Invariances and Generalization in RL (BIG@ICML'20)
    (Video presentation)(Code)
  • Biedenkapp, A. and Rajan, R. and Hutter, F. and Lindauer, M. (pdf)(slides)(bib)
    Towards TempoRL: Learning When to Act
    In: Workshop on Inductive Biases, Invariances and Generalization in RL (BIG@ICML'20)
    (Video presentation)(Code)
  • Biedenkapp, A. and Bozkurt, H. F. and Eimer, T. and Hutter, F. and Lindauer, M. (published)(pdf)(bib)
    Dynamic Algorithm Configuration: Foundation of a New Meta-Algorithmic Framework
    In: Proceedings of the Twenty-fourth European Conference on Artificial Intelligence (ECAI'20)
    (Video presentation)(Code)(Project Page)

2019

  • Lindauer, M. and Feurer, M. and Eggensperger, K. and Biedenkapp, A. and Hutter, F. (arXiv)(slides)(bib)
    Towards Assessing the Impact of Bayesian Optimization's Own Hyperparameters
    In: IJCAI 2019 DSO Workshop
  • Biedenkapp, A. and Bozkurt, H. F. and Hutter, F. and Lindauer, M. (arXiv)(pdf)(bib)
    Towards White-box Benchmarks for Algorithm Control
    In: IJCAI 2019 DSO Workshop
    (Project Page)
  • Lindauer, M. and Eggensperger, K. and Feurer, M. and Biedenkapp, A. and Marben, J. and Müller, P. and Hutter, F. (arXiv)(bib)
    BOAH: A Tool Suite for Multi-Fidelity Bayesian Optimization & Analysis of Hyperparameters
    In: arXiv:1908.06756 [cs.LG] (2019)
    (Code)(Project Page)

2018

2017

  • Biedenkapp, A. and Lindauer, M. and Eggensperger, K. and Fawcett, C. and Hoos, H. and Hutter, F. (pdf)(poster)(bib)
    Efficient Parameter Importance Analysis via Ablation with Surrogates
    In: Proceedings of the AAAI conference
    (Code)(Project Page)