Marius Lindauer
Marius Lindauer
Leibniz University Hannover (Germany)
Bestätigte E-Mail-Adresse bei tnt.uni-hannover.de - Startseite
Titel
Zitiert von
Zitiert von
Jahr
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
5112011
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
1592016
AutoFolio: an automatically configured algorithm selector
M Lindauer, HH Hoos, F Hutter, T Schaub
Journal of Artificial Intelligence Research 53, 745-778, 2015
942015
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
832011
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
662014
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
642014
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
582017
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
572018
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
552017
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
53*2015
Smac v3: Algorithm configuration in python
M Lindauer, K Eggensperger, M Feurer, S Falkner, A Biedenkapp, ...
URL https://github. com/automl/SMAC3, 2017
50*2017
Best practices for scientific research on neural architecture search
M Lindauer, F Hutter
Journal of Machine Learning Research 21 (243), 1-18, 2020
452020
Warmstarting of model-based algorithm configuration
M Lindauer, F Hutter
Thirty-Second AAAI Conference on Artificial Intelligence, 2018
442018
aspeed: Solver scheduling via answer set programming
H HOOS, R KAMINSKI, M LINDAUER, T SCHAUB
Theory and Practice of Logic Programming, 1-26, 2014
44*2014
Towards Automatically-Tuned Deep Neural Networks
H Mendoza, A Klein, M Feurer, JT Springenberg, M Urban, M Burkart, ...
Automated Machine Learning, 135-149, 2019
412019
Efficient benchmarking of algorithm configurators via model-based surrogates
K Eggensperger, M Lindauer, HH Hoos, F Hutter, K Leyton-Brown
Machine Learning, 1-27, 2018
382018
Centurio, a general game player: Parallel, Java-and ASP-based
M Möller, M Schneider, M Wegner, T Schaub
KI-Künstliche Intelligenz 25 (1), 17-24, 2011
382011
From Sequential Algorithm Selection to Parallel Portfolio Selection
M Lindauer, H Hoos, F Hutter
Proceedings of international Conference on Learning and Intelligent …, 2015
322015
The algorithm selection competitions 2015 and 2017
M Lindauer, JN van Rijn, L Kotthoff
Artificial Intelligence 272, 86-100, 2019
26*2019
Efficient Parameter Importance Analysis via Ablation with Surrogates.
A Biedenkapp, M Lindauer, K Eggensperger, F Hutter, C Fawcett, ...
AAAI, 773-779, 2017
262017
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