| Hybrid recommender system based on autoencoders F Strub, R Gaudel, J Mary Proceedings of the 1st workshop on deep learning for recommender systems, 11-16, 2016 | 288 | 2016 |
| Feature selection as a one-player game R Gaudel, M Sebag International Conference on Machine Learning, 359--366, 2010 | 122 | 2010 |
| Bandits and recommender systems J Mary, R Gaudel, P Preux Machine Learning, Optimization, and Big Data: First International Workshop …, 2015 | 87 | 2015 |
| Efficient eigen-updating for spectral graph clustering C Dhanjal, R Gaudel, S Clémençon Neurocomputing 131, 440-452, 2014 | 61 | 2014 |
| Hybrid collaborative filtering with autoencoders F Strub, J Mary, R Gaudel arXiv preprint arXiv:1603.00806, 2016 | 57 | 2016 |
| A principled method for exploiting opening books R Gaudel, JB Hoock, J Pérez, N Sokolovska, O Teytaud Computers and Games: 7th International Conference, CG 2010, Kanazawa, Japan …, 2011 | 20 | 2011 |
| s-LIME: Reconciling Locality and Fidelity in Linear Explanations R Gaudel, L Galárraga, J Delaunay, L Rozé, V Bhargava International Symposium on Intelligent Data Analysis, 102-114, 2022 | 19 | 2022 |
| Online matrix completion through nuclear norm regularisation C Dhanjal, R Gaudel, S Clémençon Proceedings of the 2014 SIAM International Conference on Data Mining, 623-631, 2014 | 17 | 2014 |
| Bandits warm-up cold recommender systems J Mary, R Gaudel, P Philippe arXiv preprint arXiv:1407.2806, 2014 | 16 | 2014 |
| Hybrid collaborative filtering with neural networks F Strub, J Mary, R Gaudel arXiv preprint arXiv:1603.00806, 2016 | 15 | 2016 |
| Unirank: Unimodal bandit algorithms for online ranking CS Gauthier, R Gaudel, E Fromont International Conference on Machine Learning, 7279-7309, 2022 | 9 | 2022 |
| Collaborative filtering with localised ranking C Dhanjal, R Gaudel, S Clémençon Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015 | 8 | 2015 |
| Incremental spectral clustering with the normalised laplacian C Dhanjal, R Gaudel, S Clémençon DISCML-3rd NIPS Workshop on Discrete Optimization in Machine Learning-2011, 2011 | 8 | 2011 |
| Scalable explore-exploit collaborative filtering F Guillou, R Gaudel, P Preux Pacific Asia Conference on Information Systems (PACIS'16), 2016 | 7 | 2016 |
| Collaborative filtering as a multi-armed bandit F Guillou, R Gaudel, P Preux NIPS'15 Workshop: Machine Learning for eCommerce, 2015 | 7 | 2015 |
| User Engagement as Evaluation: a Ranking or a Regression Problem? F Guillou, R Gaudel, J Mary, P Preux Proceedings of the 2014 Recommender Systems Challenge, 7-12, 2014 | 6 | 2014 |
| Clustering rankings in the Fourier domain S Clémençon, R Gaudel, J Jakubowicz Joint European Conference on Machine Learning and Knowledge Discovery in …, 2011 | 6 | 2011 |
| Noise variance estimation in DS-CDMA and its effects on the individually optimum receiver R Gaudel, F Bonnet, JB Domelevo-Entfellner, A Roumy 2006 IEEE 7th Workshop on Signal Processing Advances in Wireless …, 2006 | 6 | 2006 |
| Parametric graph for unimodal ranking bandit CS Gauthier, R Gaudel, E Fromont, BA Lompo International Conference on Machine Learning, 3630-3639, 2021 | 5 | 2021 |
| Large-scale bandit recommender system F Guillou, R Gaudel, P Preux Machine Learning, Optimization, and Big Data: Second International Workshop …, 2016 | 5 | 2016 |
Jeremie MARYCriteo AI LabVerified email at criteo.com
