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Herilalaina Rakotoarison
Herilalaina Rakotoarison
University of Freiburg
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Cited by
Cited by
Year
Automated Machine Learning with Monte-Carlo Tree Search
H Rakotoarison, M Schoenauer, M Sebag
International Joint Conference on Artificial Intelligence 2019, 2019
722019
Black-box optimization revisited: Improving algorithm selection wizards through massive benchmarking
L Meunier, H Rakotoarison, PK Wong, B Roziere, J Rapin, O Teytaud, ...
IEEE Transactions on Evolutionary Computation 26 (3), 490-500, 2021
452021
Efficient bayesian learning curve extrapolation using prior-data fitted networks
S Adriaensen, H Rakotoarison, S Müller, F Hutter
Thirty-seventh Annual Conference on Neural Information Processing Systems, 2023
232023
Learning meta-features for AutoML
H Rakotoarison, L Milijaona, A Rasoanaivo, M Sebag, M Schoenauer
International Conference on Learning Representations (ICLR) 2022, 2022
212022
In-Context Freeze-Thaw Bayesian Optimization for Hyperparameter Optimization
H Rakotoarison, S Adriaensen, N Mallik, S Garibov, E Bergman, F Hutter
International Conference on Machine Learning (ICML), 2024
82024
AutoML with Monte Carlo Tree Search
H Rakotoarison, M Sebag
AutoML@ICML 2018, 2018
82018
Distribution-based invariant deep networks for learning meta-features
G De Bie, H Rakotoarison, G Peyré, M Sebag
arXiv preprint arXiv:2006.13708, 2020
42020
Some contributions to AutoML: hyper-parameter optimization and meta-learning
H Rakotoarison
Université Paris-Saclay, 2022
12022
Warmstarting for Scaling Language Models
N Mallik, M Janowski, J Hog, H Rakotoarison, A Klein, J Grabocka, ...
arXiv preprint arXiv:2411.07340, 2024
2024
Results from the Joint Nevergrad and IOHprofiler Open Optimization Competition
T Bäck, P Bennet, J de Nobel, C Doerr, J Dreo, H Rakotoarison, J Rapin, ...
2021
From Epoch to Sample Size: Developing New Data-driven Priors for Learning Curve Prior-Fitted Networks
TJ Viering, S Adriaensen, H Rakotoarison, F Hutter
AutoML Conference 2024 (Workshop Track), 0
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Articles 1–11