André Biedenkapp

47 papers A* 7A 4Journal 33Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	A Llama walks into the 'Bar': Efficient Supervised Fine-Tuning for Legal Reasoning in the Multi-state Bar Exam. CoRR Rean Fernandes, André Biedenkapp, Frank Hutter, Noor H. Awad
2025	J	`jnl`	Best Practices For Empirical Meta-Algorithmic Research: Guidelines from the COSEAL Research Network. CoRR Theresa Eimer, Lennart Schäpermeier, André Biedenkapp, Alexander Tornede, Lars Kotthoff, Pieter Leyman, Matthias Feurer, Katharina Eggensperger, Kaitlin Maile, Tanja Tornede, Anna Kozak, Ke Xue, Marcel Wever, Mitra Baratchi, Damir Pulatov, Heike Trautmann, Haniye Kashgarani, Marius Lindauer
2025	J	`jnl`	Deep Reinforcement Learning for Dynamic Algorithm Configuration: A Case Study on Optimizing OneMax with the (1+(λ,λ))-GA. CoRR Tai Nguyen, Phong Le, André Biedenkapp, Carola Doerr, Nguyen Dang
2025	A*	`conf`	Efficient Cross-Episode Meta-RL. ICLR Gresa Shala, André Biedenkapp, Pierre Krack, Florian Walter, Josif Grabocka
2025	J	`jnl`	Meta-learning Population-based Methods for Reinforcement Learning. Trans. Mach. Learn. Res. Johannes Hog, Raghu Rajan, André Biedenkapp, Noor H. Awad, Frank Hutter, Vu Nguyen
2025	A	`conf`	On the Importance of Reward Design in Reinforcement Learning-based Dynamic Algorithm Configuration: A Case Study on OneMax with (1+(λ, λ))-GA. GECCO Tai Nguyen, Phong Le, André Biedenkapp, Carola Doerr, Nguyen Dang
2025	J	`jnl`	On the Importance of Reward Design in Reinforcement Learning-based Dynamic Algorithm Configuration: A Case Study on OneMax with (1+(λ,λ))-GA. CoRR Tai Nguyen, Phong Le, André Biedenkapp, Carola Doerr, Nguyen Dang
2024	J	`jnl`	CANDID DAC: Leveraging Coupled Action Dimensions with Importance Differences in DAC. CoRR Philipp Bordne, M. Asif Hasan, Eddie Bergman, Noor H. Awad, André Biedenkapp
2024	J	`jnl`	Dreaming of Many Worlds: Learning Contextual World Models Aids Zero-Shot Generalization. CoRR Sai Prasanna, Karim Farid, Raghu Rajan, André Biedenkapp
2024	J	`jnl`	Dreaming of Many Worlds: Learning Contextual World Models aids Zero-Shot Generalization. RLJ Sai Prasanna, Karim Farid, Raghu Rajan, André Biedenkapp
2024	—	`conf`	HPO-RL-Bench: A Zero-Cost Benchmark for HPO in Reinforcement Learning. AutoML Gresa Shala, Sebastian Pineda-Arango, André Biedenkapp, Frank Hutter, Josif Grabocka
2024	J	`jnl`	Hierarchical Transformers are Efficient Meta-Reinforcement Learners. CoRR Gresa Shala, André Biedenkapp, Josif Grabocka
2024	J	`jnl`	Inferring Behavior-Specific Context Improves Zero-Shot Generalization in Reinforcement Learning. CoRR Tidiane Camaret Ndir, André Biedenkapp, Noor H. Awad
2023	J	`jnl`	Contextualize Me - The Case for Context in Reinforcement Learning. Trans. Mach. Learn. Res. Carolin Benjamins, Theresa Eimer, Frederik Schubert, Aditya Mohan, Sebastian Döhler, André Biedenkapp, Bodo Rosenhahn, Frank Hutter, Marius Lindauer
2023	A*	`conf`	Gray-Box Gaussian Processes for Automated Reinforcement Learning. ICLR Gresa Shala, André Biedenkapp, Frank Hutter, Josif Grabocka
2023	J	`jnl`	MDP Playground: An Analysis and Debug Testbed for Reinforcement Learning. J. Artif. Intell. Res. Raghu Rajan, Jessica Lizeth Borja Diaz, Suresh Guttikonda, Fabio Ferreira, André Biedenkapp, Jan Ole von Hartz, Frank Hutter
2022	J	`jnl`	Automated Dynamic Algorithm Configuration. CoRR Steven Adriaensen, André Biedenkapp, Gresa Shala, Noor H. Awad, Theresa Eimer, Marius Lindauer, Frank Hutter
2022	J	`jnl`	Automated Dynamic Algorithm Configuration. J. Artif. Intell. Res. Steven Adriaensen, André Biedenkapp, Gresa Shala, Noor H. Awad, Theresa Eimer, Marius Lindauer, Frank Hutter
2022	J	`jnl`	Automated Reinforcement Learning (AutoRL): A Survey and Open Problems. CoRR 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
2022	J	`jnl`	Automated Reinforcement Learning (AutoRL): A Survey and Open Problems. J. Artif. Intell. Res. 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
2022	J	`jnl`	Contextualize Me - The Case for Context in Reinforcement Learning. CoRR Carolin Benjamins, Theresa Eimer, Frederik Schubert, Aditya Mohan, André Biedenkapp, Bodo Rosenhahn, Frank Hutter, Marius Lindauer
2022	J	`jnl`	DeepCAVE: An Interactive Analysis Tool for Automated Machine Learning. CoRR René Sass, Eddie Bergman, André Biedenkapp, Frank Hutter, Marius Lindauer
2022	—	`—`	Dynamic algorithm configuration by reinforcement learning. André Biedenkapp
2022	J	`jnl`	SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization. J. Mach. Learn. Res. Marius Lindauer, Katharina Eggensperger, Matthias Feurer, André Biedenkapp, Difan Deng, Carolin Benjamins, Tim Ruhkopf, René Sass, Frank Hutter
2022	J	`jnl`	Theory-inspired Parameter Control Benchmarks for Dynamic Algorithm Configuration. CoRR André Biedenkapp, Nguyen Dang, Martin S. Krejca, Frank Hutter, Carola Doerr
2022	A	`conf`	Theory-inspired parameter control benchmarks for dynamic algorithm configuration. GECCO André Biedenkapp, Nguyen Dang, Martin S. Krejca, Frank Hutter, Carola Doerr
2021	J	`jnl`	CARL: A Benchmark for Contextual and Adaptive Reinforcement Learning. CoRR Carolin Benjamins, Theresa Eimer, Frederik Schubert, André Biedenkapp, Bodo Rosenhahn, Frank Hutter, Marius Lindauer
2021	A*	`conf`	DACBench: A Benchmark Library for Dynamic Algorithm Configuration. IJCAI Theresa Eimer, André Biedenkapp, Maximilian Reimer, Steven Adriaensen, Frank Hutter, Marius Lindauer
2021	J	`jnl`	DACBench: A Benchmark Library for Dynamic Algorithm Configuration. CoRR Theresa Eimer, André Biedenkapp, Maximilian Reimer, Steven Adriaensen, Frank Hutter, Marius Lindauer
2021	J	`jnl`	In-Loop Meta-Learning with Gradient-Alignment Reward. CoRR Samuel Müller, André Biedenkapp, Frank Hutter
2021	A*	`conf`	Learning Heuristic Selection with Dynamic Algorithm Configuration. ICAPS David Speck, André Biedenkapp, Frank Hutter, Robert Mattmüller, Marius Lindauer
2021	A	`conf`	On the Importance of Hyperparameter Optimization for Model-based Reinforcement Learning. AISTATS Baohe Zhang, Raghu Rajan, Luis Pineda, Nathan O. Lambert, André Biedenkapp, Kurtland Chua, Frank Hutter, Roberto Calandra
2021	J	`jnl`	On the Importance of Hyperparameter Optimization for Model-based Reinforcement Learning. CoRR Baohe Zhang, Raghu Rajan, Luis Pineda, Nathan O. Lambert, André Biedenkapp, Kurtland Chua, Frank Hutter, Roberto Calandra
2021	J	`jnl`	SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization. CoRR Marius Lindauer, Katharina Eggensperger, Matthias Feurer, André Biedenkapp, Difan Deng, Carolin Benjamins, René Sass, Frank Hutter
2021	A*	`conf`	Sample-Efficient Automated Deep Reinforcement Learning. ICLR Jörg K. H. Franke, Gregor Köhler, André Biedenkapp, Frank Hutter
2021	A*	`conf`	Self-Paced Context Evaluation for Contextual Reinforcement Learning. ICML Theresa Eimer, André Biedenkapp, Frank Hutter, Marius Lindauer
2021	J	`jnl`	Self-Paced Context Evaluation for Contextual Reinforcement Learning. CoRR Theresa Eimer, André Biedenkapp, Frank Hutter, Marius Lindauer
2021	A*	`conf`	TempoRL: Learning When to Act. ICML André Biedenkapp, Raghu Rajan, Frank Hutter, Marius Lindauer
2021	J	`jnl`	TempoRL: Learning When to Act. CoRR André Biedenkapp, Raghu Rajan, Frank Hutter, Marius Lindauer
2020	A	`conf`	Dynamic Algorithm Configuration: Foundation of a New Meta-Algorithmic Framework. ECAI André Biedenkapp, H. Furkan Bozkurt, Theresa Eimer, Frank Hutter, Marius Lindauer
2020	J	`jnl`	Learning Heuristic Selection with Dynamic Algorithm Configuration. CoRR David Speck, André Biedenkapp, Frank Hutter, Robert Mattmüller, Marius Lindauer
2020	—	`conf`	Learning Step-Size Adaptation in CMA-ES. PPSN (1) Gresa Shala, André Biedenkapp, Noor H. Awad, Steven Adriaensen, Marius Lindauer, Frank Hutter
2020	J	`jnl`	Sample-Efficient Automated Deep Reinforcement Learning. CoRR Jörg K. H. Franke, Gregor Köhler, André Biedenkapp, Frank Hutter
2020	J	`jnl`	Squirrel: A Switching Hyperparameter Optimizer. CoRR Noor H. Awad, Gresa Shala, Difan Deng, Neeratyoy Mallik, Matthias Feurer, Katharina Eggensperger, André Biedenkapp, Diederick Vermetten, Hao Wang, Carola Doerr, Marius Lindauer, Frank Hutter
2019	J	`jnl`	BOAH: A Tool Suite for Multi-Fidelity Bayesian Optimization & Analysis of Hyperparameters. CoRR Marius Lindauer, Katharina Eggensperger, Matthias Feurer, André Biedenkapp, Joshua Marben, Philipp Müller, Frank Hutter
2019	J	`jnl`	Towards Assessing the Impact of Bayesian Optimization's Own Hyperparameters. CoRR Marius Lindauer, Matthias Feurer, Katharina Eggensperger, André Biedenkapp, Frank Hutter
2019	J	`jnl`	Towards White-box Benchmarks for Algorithm Control. CoRR André Biedenkapp, H. Furkan Bozkurt, Frank Hutter, Marius Lindauer