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Michele Sebag
Michele Sebag
Senior Researcher
Adresse e-mail validée de lri.fr - Page d'accueil
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Année
Collaborative hyperparameter tuning
R Bardenet, M Brendel, B Kégl, M Sebag
International conference on machine learning, 199-207, 2013
4672013
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
3172012
Extending population-based incremental learning to continuous search spaces
M Sebag, A Ducoulombier
International Conference on Parallel Problem Solving from Nature, 418-427, 1998
3161998
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
2822002
Causal generative neural networks
O Goudet, D Kalainathan, P Caillou, I Guyon, D Lopez-Paz, M Sebag
arXiv preprint arXiv:1711.08936, 2017
218*2017
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
1972008
Preference-based policy learning
R Akrour, M Schoenauer, M Sebag
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2011
1792011
April: Active preference learning-based reinforcement learning
R Akrour, M Schoenauer, M Sebag
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2012
1772012
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
1752018
Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2010, Barcelona, Spain, September 20-24, 2010. Proceedings, Part III
JL Balcázar, F Bonchi, A Gionis, M Sebag
Springer, 2010
175*2010
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
1742010
Exploration vs exploitation vs safety: Risk-aware multi-armed bandits
N Galichet, M Sebag, O Teytaud
Asian Conference on Machine Learning, 245-260, 2013
1492013
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
1472019
Analysis of the AutoML Challenge Series
I Guyon, L Sun-Hosoya, M Boullé, HJ Escalante, S Escalera, Z Liu, ...
Automated Machine Learning, 177, 2019
1472019
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
1372008
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
1362012
Multi-armed bandit, dynamic environments and meta-bandits
C Hartland, S Gelly, N Baskiotis, O Teytaud, M Sebag
1252006
Feature selection as a one-player game
R Gaudel, M Sebag
International Conference on Machine Learning, 359--366, 2010
1192010
Data streaming with affinity propagation
X Zhang, C Furtlehner, M Sebag
Joint European Conference on Machine Learning and Knowledge Discovery in …, 2008
1192008
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
1172013
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