Marius Lindauer
Marius Lindauer
Other namesMarius Schneider
Leibniz University Hannover (Germany), Institute of Artificial Intelligence LUH|AI, L3S Research
Verified email at - Homepage
Cited by
Cited by
Potassco: The Potsdam answer set solving collection
M Gebser, B Kaufmann, R Kaminski, M Ostrowski, T Schaub, M Schneider
AI Communications 24 (2), 107-124, 2011
Auto-sklearn 2.0: Hands-free automl via meta-learning
M Feurer, K Eggensperger, S Falkner, M Lindauer, F Hutter
Journal of Machine Learning Research (JMLR), 2022
Hyperparameter optimization: Foundations, algorithms, best practices, and open challenges
B Bischl, M Binder, M Lang, T Pielok, J Richter, S Coors, J Thomas, ...
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 13 (2 …, 2023
Aslib: A benchmark library for algorithm selection
B Bischl, P Kerschke, L Kotthoff, M Lindauer, Y Malitsky, A Fréchette, ...
Artificial Intelligence 237, 41-58, 2016
SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization.
M Lindauer, K Eggensperger, M Feurer, A Biedenkapp, D Deng, ...
J. Mach. Learn. Res. 23, 54:1-54:9, 2022
Auto-Pytorch: Multi-Fidelity MetaLearning for Efficient and Robust AutoDL.
L Zimmer, M Lindauer, F Hutter
IEEE Transactions on Pattern Analysis and Machine Intelligence 43 (9), 3079 …, 2021
Well-tuned Simple Nets Excel on Tabular Datasets
A Kadra, M Lindauer, F Hutter, J Grabocka
Advances in Neural Information Processing Systems 34, 2021
AutoFolio: an automatically configured algorithm selector
M Lindauer, HH Hoos, F Hutter, T Schaub
Journal of Artificial Intelligence Research 53, 745-778, 2015
Best practices for scientific research on neural architecture search
M Lindauer, F Hutter
Journal of Machine Learning Research 21 (243), 1-18, 2020
Practical automated machine learning for the automl challenge 2018
M Feurer, K Eggensperger, S Falkner, M Lindauer, F Hutter
International Workshop on Automatic Machine Learning at ICML, 1189-1232, 2018
A portfolio solver for answer set programming: Preliminary report
M Gebser, R Kaminski, B Kaufmann, T Schaub, MT Schneider, S Ziller
International Conference on Logic Programming and Nonmonotonic Reasoning …, 2011
claspfolio 2: Advances in Algorithm Selection for Answer Set Programming
H Hoos, M Lindauer, T Schaub
Theory and Practice of Logic Programming 14 (Special Issue 4-5), 569--585, 2014
AClib: A benchmark library for algorithm configuration
F Hutter, M López-Ibánez, C Fawcett, M Lindauer, HH Hoos, ...
International Conference on Learning and Intelligent Optimization, 36-40, 2014
Potassco User Guide
M Gebser, R Kaminski, B Kaufmann, M Lindauer, M Ostrowski, J Romero, ...
Institute for Informatics, University of Potsdam, second edition edition, 2015
HPOBench: A Collection of Reproducible Multi-Fidelity Benchmark Problems for HPO
K Eggensperger, P Müller, N Mallik, M Feurer, R Sass, A Klein, N Awad, ...
NeurIPS Track Datasets and Benchmarks, 2021
A case study of algorithm selection for the traveling thief problem
M Wagner, M Lindauer, M Mısır, S Nallaperuma, F Hutter
Journal of Heuristics, 1-26, 2017
The configurable SAT solver challenge (CSSC)
F Hutter, M Lindauer, A Balint, S Bayless, H Hoos, K Leyton-Brown
Artificial Intelligence 243, 1-25, 2017
Warmstarting of model-based algorithm configuration
M Lindauer, F Hutter
Thirty-Second AAAI Conference on Artificial Intelligence, 2018
Automated reinforcement learning (autorl): A survey and open problems
J Parker-Holder, R Rajan, X Song, A Biedenkapp, Y Miao, T Eimer, ...
Journal of Artificial Intelligence Research 74, 517-568, 2022
Dynamic Algorithm Configuration: Foundation of a New Meta-Algorithmic Framework
A Biedenkapp, HF Bozkurt, T Eimer, F Hutter, M Lindauer
European Conference on AI (ECAI), 2020
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