| Parallel Gaussian Process Optimization with Upper Confidence Bound and Pure Exploration E Contal, D Buffoni, A Robicquet, N Vayatis Machine Learning and Knowledge Discovery in Databases, 225-240, 2013 | 232 | 2013 |
| Preface to ECML PKDD 2014: Joint European Conference on Machine Learning and Knowledge Discovery in Databases T Calders, F Esposito, E Hüllermeier, R Meo Springer 8724 (1, 2, 3), 111-749, 2014 | 151 | 2014 |
| Gaussian Process Optimization with Mutual Information E Contal, V Perchet, N Vayatis Proceedings of The 31st International Conference on Machine Learning, 253-261, 2014 | 118 | 2014 |
| Beyond skill rating: Advanced matchmaking in ghost recon online O Delalleau, E Contal, E Thibodeau-Laufer, RC Ferrari, Y Bengio, ... IEEE Transactions on Computational Intelligence and AI in Games 4 (3), 167-177, 2012 | 117 | 2012 |
| Prediction and optimization of wave energy converter arrays using a machine learning approach D Sarkar, E Contal, N Vayatis, F Dias Renewable Energy 97, 504-517, 2016 | 95 | 2016 |
| Can small islands protect nearby coasts from tsunamis? An active experimental design approach TS Stefanakis, E Contal, N Vayatis, F Dias, CE Synolakis Proceedings of the Royal Society A: Mathematical, Physical and Engineering …, 2014 | 55 | 2014 |
| Preprocessing the Nintendo Wii board signal to derive more accurate descriptors of statokinesigrams J Audiffren, E Contal Sensors 16 (8), 1208, 2016 | 40 | 2016 |
| A ranking approach to global optimization C Malherbe, E Contal, N Vayatis International Conference on Machine Learning, 1539-1547, 2016 | 14 | 2016 |
| Optimization for gaussian processes via chaining E Contal, C Malherbe, N Vayatis arXiv preprint arXiv:1510.05576, 2015 | 12 | 2015 |
| Stochastic process bandits: Upper confidence bounds algorithms via generic chaining E Contal, N Vayatis arXiv preprint arXiv:1602.04976, 2016 | 8 | 2016 |
| Machine Learning and Knowledge Discovery in Databases, chapter Parallel Gaussian Process Optimization with Upper Confidence Bound and Pure Exploration E Contal, D Buffoni, A Robicquet, N Vayatis Springer Berlin Heidelberg, 2013 | 6 | 2013 |
| Parallel Gaussian Process optimization with pure exploration E Contal, D Buffoni, A Robicquet, N Vayatis Proceedings of ICML (pending approval) 74, 80-81, 2013 | 6 | 2013 |
| Statistical learning approaches for global optimization E Contal Université Paris Saclay (COmUE), 2016 | 5 | 2016 |
| A machine learning approach to the analysis of wave energy converters D Sarkar, E Contal, N Vayatis, F Dias International Conference on Offshore Mechanics and Arctic Engineering 56574 …, 2015 | 4 | 2015 |
| RAGSys: Item-Cold-Start Recommender as RAG System E Contal, G McGoldrick arXiv preprint arXiv:2405.17587, 2024 | 1 | 2024 |
| Gaussian processes for computer experiments F Bachoc, E Contal, H Maatouk, D Rullière ESAIM: Proceedings and Surveys 60, 163-179, 2017 | 1 | 2017 |
| Can small islands protect nearby coasts from TS Stefanakis, E Contal, N Vayatis, F Dias, CE Synolakis | | |
| New methods for sensitivity analysis and uncertainty quantification of tsunamis F Dias, S Guillas, N Vayatis, A Sarri, TS Stefanakis, E Contal, ... | | |
