Biedenkapp, André

19 publications

ICLR 2025 Efficient Cross-Episode Meta-RL Gresa Shala, André Biedenkapp, Pierre Krack, Florian Walter, Josif Grabocka

TMLR 2025 Meta-Learning Population-Based Methods for Reinforcement Learning Johannes Hog, Raghu Rajan, André Biedenkapp, Noor Awad, Frank Hutter, Vu Nguyen

AutoML 2024 HPO-RL-Bench: A Zero-Cost Benchmark for HPO in Reinforcement Learning Gresa Shala, Sebastian Pineda Arango, André Biedenkapp, Frank Hutter, Josif Grabocka

NeurIPSW 2024 One-Shot World Models Using a Transformer Trained on a Synthetic Prior Fabio Ferreira, Moreno Schlageter, Raghu Rajan, André Biedenkapp, Frank Hutter

TMLR 2023 Contextualize Me – The Case for Context in Reinforcement Learning Carolin Benjamins, Theresa Eimer, Frederik Schubert, Aditya Mohan, Sebastian Döhler, André Biedenkapp, Bodo Rosenhahn, Frank Hutter, Marius Lindauer

ICLR 2023 Gray-Box Gaussian Processes for Automated Reinforcement Learning Gresa Shala, André Biedenkapp, Frank Hutter, Josif Grabocka

JAIR 2023 MDP Playground: An Analysis and Debug Testbed for Reinforcement Learning Raghu Rajan, Jessica Lizeth Borja Diaz, Suresh Guttikonda, Fabio Ferreira, André Biedenkapp, Jan Ole von Hartz, Frank Hutter

NeurIPSW 2022 AutoRL-Bench 1.0 Gresa Shala, Sebastian Pineda Arango, André Biedenkapp, Frank Hutter, Josif Grabocka

JAIR 2022 Automated Dynamic Algorithm Configuration Steven Adriaensen, André Biedenkapp, Gresa Shala, Noor H. Awad, Theresa Eimer, Marius Lindauer, Frank Hutter

JAIR 2022 Automated Reinforcement Learning (AutoRL): A Survey and Open Problems 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

NeurIPSW 2022 Gray-Box Gaussian Processes for Automated Reinforcement Learning Gresa Shala, André Biedenkapp, Frank Hutter, Josif Grabocka

MLOSS 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

AISTATS 2021 On the Importance of Hyperparameter Optimization for Model-Based Reinforcement Learning Baohe Zhang, Raghu Rajan, Luis Pineda, Nathan Lambert, André Biedenkapp, Kurtland Chua, Frank Hutter, Roberto Calandra

ICMLW 2021 Bag of Baselines for Multi-Objective Joint Neural Architecture Search and Hyperparameter Optimization Sergio Izquierdo, Julia Guerrero-Viu, Sven Hauns, Guilherme Miotto, Simon Schrodi, André Biedenkapp, Thomas Elsken, Difan Deng, Marius Lindauer, Frank Hutter

IJCAI 2021 DACBench: A Benchmark Library for Dynamic Algorithm Configuration Theresa Eimer, André Biedenkapp, Maximilian Reimer, Steven Adriaensen, Frank Hutter, Marius Lindauer

ICLR 2021 Sample-Efficient Automated Deep Reinforcement Learning Jörg K.H. Franke, Gregor Koehler, André Biedenkapp, Frank Hutter

ICML 2021 Self-Paced Context Evaluation for Contextual Reinforcement Learning Theresa Eimer, André Biedenkapp, Frank Hutter, Marius Lindauer

ICML 2021 TempoRL: Learning When to Act André Biedenkapp, Raghu Rajan, Frank Hutter, Marius Lindauer

AAAI 2017 Efficient Parameter Importance Analysis via Ablation with Surrogates Andre Biedenkapp, Marius Lindauer, Katharina Eggensperger, Frank Hutter, Chris Fawcett, Holger H. Hoos