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Michele Sebag
Michele Sebag
Senior Researcher
Dirección de correo verificada de lri.fr - Página principal
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Citado por
Citado por
Año
Collaborative hyperparameter tuning
R Bardenet, M Brendel, B Kégl, M Sebag
International conference on machine learning, 199-207, 2013
5142013
Extending population-based incremental learning to continuous search spaces
M Sebag, A Ducoulombier
International Conference on Parallel Problem Solving from Nature, 418-427, 1998
3261998
The grand challenge of computer Go: Monte Carlo tree search and extensions
S Gelly, L Kocsis, M Schoenauer, M Sebag, D Silver, C Szepesvári, ...
Communications of the ACM 55 (3), 106-113, 2012
3252012
Treefinder: a first step towards xml data mining
A Termier, MC Rousset, M Sebag
2002 IEEE International Conference on Data Mining, 2002. Proceedings., 450-457, 2002
2832002
Causal generative neural networks
O Goudet, D Kalainathan, P Caillou, I Guyon, D Lopez-Paz, M Sebag
arXiv preprint arXiv:1711.08936, 2017
232*2017
April: Active preference learning-based reinforcement learning
R Akrour, M Schoenauer, M Sebag
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2012
2062012
Preference-based policy learning
R Akrour, M Schoenauer, M Sebag
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2011
1992011
Adaptive operator selection with dynamic multi-armed bandits
L DaCosta, A Fialho, M Schoenauer, M Sebag
Proceedings of the 10th annual conference on Genetic and evolutionary …, 2008
1992008
Learning functional causal models with generative neural networks
O Goudet, D Kalainathan, P Caillou, I Guyon, D Lopez-Paz, M Sebag
Explainable and Interpretable Models in Computer Vision and Machine Learning …, 2018
1822018
Analyzing bandit-based adaptive operator selection mechanisms
A Fialho, L Da Costa, M Schoenauer, M Sebag
Annals of Mathematics and Artificial Intelligence 60 (1), 25-64, 2010
1822010
Analysis of the AutoML Challenge Series 2015–2018
I Guyon, L Sun-Hosoya, M Boullé, HJ Escalante, S Escalera, Z Liu, ...
Automated Machine Learning, 177-219, 2019
1642019
Analysis of the AutoML Challenge Series
I Guyon, L Sun-Hosoya, M Boullé, HJ Escalante, S Escalera, Z Liu, ...
Automated Machine Learning, 177, 2019
1642019
Exploration vs exploitation vs safety: Risk-aware multi-armed bandits
N Galichet, M Sebag, O Teytaud
Asian Conference on Machine Learning, 245-260, 2013
1532013
BenchNN: On the broad potential application scope of hardware neural network accelerators
T Chen, Y Chen, M Duranton, Q Guo, A Hashmi, M Lipasti, A Nere, S Qiu, ...
2012 IEEE International Symposium on Workload Characterization (IISWC), 36-45, 2012
1392012
Extreme value based adaptive operator selection
Á Fialho, L Da Costa, M Schoenauer, M Sebag
International Conference on Parallel Problem Solving from Nature, 175-184, 2008
1392008
Comparison-based optimizers need comparison-based surrogates
I Loshchilov, M Schoenauer, M Sebag
International Conference on Parallel Problem Solving from Nature, 364-373, 2010
1292010
Multi-armed bandit, dynamic environments and meta-bandits
C Hartland, S Gelly, N Baskiotis, O Teytaud, M Sebag
1292006
Feature selection as a one-player game
R Gaudel, M Sebag
International Conference on Machine Learning, 359--366, 2010
1222010
Data stream clustering with affinity propagation
X Zhang, C Furtlehner, C Germain-Renaud, M Sebag
IEEE Transactions on Knowledge and Data Engineering 26 (7), 1644-1656, 2013
1192013
Data streaming with affinity propagation
X Zhang, C Furtlehner, M Sebag
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2008
1192008
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Artículos 1–20