francis maes
francis maes
Postdoctoral fellow, University of Leuven, Belgium
Bestätigte E-Mail-Adresse bei - Startseite
Zitiert von
Zitiert von
Learning exploration/exploitation strategies for single trajectory reinforcement learning
M Castronovo, F Maes, R Fonteneau, D Ernst
European Workshop on Reinforcement Learning, 1-10, 2013
Comparison of different selection strategies in monte-carlo tree search for the game of tron
P Perick, DL St-Pierre, F Maes, D Ernst
2012 IEEE Conference on Computational Intelligence and Games (CIG), 242-249, 2012
Structured prediction with reinforcement learning
F Maes, L Denoyer, P Gallinari
Machine learning 77, 271-301, 2009
Policy search in a space of simple closed-form formulas: Towards interpretability of reinforcement learning
F Maes, R Fonteneau, L Wehenkel, D Ernst
Discovery Science: 15th International Conference, DS 2012, Lyon, France …, 2012
Meta-learning of exploration/exploitation strategies: The multi-armed bandit case
F Maes, L Wehenkel, D Ernst
Agents and Artificial Intelligence: 4th International Conference, ICAART …, 2013
Automatic discovery of ranking formulas for playing with multi-armed bandits
F Maes, L Wehenkel, D Ernst
Recent Advances in Reinforcement Learning: 9th European Workshop, EWRL 2011 …, 2012
Simulated iterative classification a new learning procedure for graph labeling
F Maes, S Peters, L Denoyer, P Gallinari
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2009
Learning to play K-armed bandit problems
F Maes, L Wehenkel, D Ernst
4th International Conference on Agents and Artificial Intelligence (ICAART 2012), 2012
Monte carlo search algorithm discovery for single-player games
F Maes, DL St-Pierre, D Ernst
IEEE Transactions on Computational Intelligence and AI in Games 5 (3), 201-213, 2013
Multi-objective optimization with surrogate trees
D Verbeeck, F Maes, K De Grave, H Blockeel
Proceedings of the 15th annual conference on Genetic and evolutionary …, 2013
Sequence labeling with reinforcement learning and ranking algorithms
F Maes, L Denoyer, P Gallinari
European Conference on Machine Learning, 648-657, 2007
On the encoding of proteins for disordered regions prediction
J Becker, F Maes, L Wehenkel
PloS one 8 (12), e82252, 2013
Optimized look-ahead tree policies
F Maes, L Wehenkel, D Ernst
Proceedings of the 9th European Workshop on Reinforcement Learning (EWRL 2011), 2011
On the relevance of sophisticated structural annotations for disulfide connectivity pattern prediction
J Becker, F Maes, L Wehenkel
PLoS One 8 (2), e56621, 2013
Embedding Monte Carlo search of features in tree-based ensemble methods
F Maes, P Geurts, L Wehenkel
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2012
Learning in Markov decision processes for structured prediction
F Maes
PhD thesis, Pierre and Marie Curie University, Computer Science Laboratory …, 2009
XML Structure Mapping: Application to the PASCAL/INEX 2006 XML Document Mining Track
F Maes, L Denoyer, P Gallinari
International Workshop of the Initiative for the Evaluation of XML Retrieval …, 2006
Optimized look‐ahead tree policies: a bridge between look‐ahead tree policies and direct policy search
T Jung, L Wehenkel, D Ernst, F Maes
International Journal of Adaptive Control and Signal Processing 28 (3-5 …, 2014
Exploring the space of IR functions
P Goswami, S Moura, E Gaussier, MR Amini, F Maes
Advances in Information Retrieval: 36th European Conference on IR Research …, 2014
Modèle probabiliste pour l'extraction de structures dans les documents semi-structurés: Application aux documents Web
G Wisniewski, L Denoyer, F Maes, P Gallinari
3eme Conference en Recherche d'Information et Applications (CORIA'06), 169-180, 2006
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