| Co-clustering through optimal transport C Laclau, I Redko, B Matei, Y Bennani, V Brault International conference on machine learning, 1955-1964, 2017 | 59 | 2017 |
| All of the fairness for edge prediction with optimal transport C Laclau, I Redko, M Choudhary, C Largeron International Conference on Artificial Intelligence and Statistics, 1774-1782, 2021 | 55 | 2021 |
| User preference and embedding learning with implicit feedback for recommender systems S Sidana, M Trofimov, O Horodnytskyi, C Laclau, Y Maximov, MR Amini Data Mining and Knowledge Discovery 35, 568-592, 2021 | 46* | 2021 |
| A survey on fairness for machine learning on graphs C Laclau, C Largeron, M Choudhary arXiv preprint arXiv:2205.05396, 2022 | 36 | 2022 |
| KASANDR: a large-scale dataset with implicit feedback for recommendation S Sidana, C Laclau, MR Amini, G Vandelle, A Bois-Crettez Proceedings of the 40th International ACM SIGIR Conference on Research and …, 2017 | 32 | 2017 |
| Learning to recommend diverse items over implicit feedback on PANDOR S Sidana, C Laclau, MR Amini Proceedings of the 12th ACM Conference on Recommender Systems, 427-431, 2018 | 28 | 2018 |
| Hard and fuzzy diagonal co-clustering for document-term partitioning C Laclau, M Nadif Neurocomputing 193, 133-147, 2016 | 26 | 2016 |
| Cross-lingual document retrieval using regularized wasserstein distance G Balikas, C Laclau, I Redko, MR Amini Advances in Information Retrieval: 40th European Conference on IR Research …, 2018 | 19 | 2018 |
| Diagonal latent block model for binary data C Laclau, M Nadif Statistics and Computing 27, 1145-1163, 2017 | 10 | 2017 |
| Fuzzy co-clustering with automated variable weighting C Laclau, FAT de Carvalho, M Nadif 2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 1-8, 2015 | 8 | 2015 |
| Noise-free latent block model for high dimensional data C Laclau, V Brault Data Mining and Knowledge Discovery 33, 446-473, 2019 | 7 | 2019 |
| On fair cost sharing games in machine learning I Redko, C Laclau Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 4790-4797, 2019 | 5 | 2019 |
| Learning over no-preferred and preferred sequence of items for robust recommendation A Burashnikova, Y Maximov, M Clausel, C Laclau, F Iutzeler, MR Amini Journal of Artificial Intelligence Research 71, 121-142, 2021 | 4 | 2021 |
| Deep neural networks are congestion games: From loss landscape to Wardrop equilibrium and beyond N Vesseron, I Redko, C Laclau International Conference on Artificial Intelligence and Statistics, 1765-1773, 2021 | 4 | 2021 |
| Fast simultaneous clustering and feature selection for binary data C Laclau, M Nadif Advances in Intelligent Data Analysis XIII: 13th International Symposium …, 2014 | 4 | 2014 |
| Fair Text Classification with Wasserstein Independence T Leteno, A Gourru, C Laclau, R Emonet, C Gravier EMNLP, 2023 | 3 | 2023 |
| From alexnet to transformers: Measuring the non-linearity of deep neural networks with affine optimal transport Q Bouniot, I Redko, A Mallasto, C Laclau, K Arndt, O Struckmeier, ... arXiv preprint arXiv:2310.11439, 2023 | 3 | 2023 |
| An investigation of structures responsible for gender bias in BERT and DistilBERT T Leteno, A Gourru, C Laclau, C Gravier International symposium on intelligent data analysis, 249-261, 2023 | 3 | 2023 |
| Diagonal co-clustering algorithm for document-word partitioning C Laclau, M Nadif Advances in Intelligent Data Analysis XIV: 14th International Symposium, IDA …, 2015 | 3 | 2015 |
| A Study on Hierarchical Text Classification as a Seq2seq Task F Torba, C Gravier, C Laclau, A Kammoun, J Subercaze European Conference on Information Retrieval, 287-296, 2024 | 2 | 2024 |
