| Imputation and low-rank estimation with missing not at random data A Sportisse, C Boyer, J Josse Statistics and Computing 30 (6), 1629-1643, 2020 | 51 | 2020 |
| Estimation and imputation in probabilistic principal component analysis with missing not at random data A Sportisse, C Boyer, J Josse Advances in Neural Information Processing Systems 33, 7067-7077, 2020 | 33 | 2020 |
| R-miss-tastic: a unified platform for missing values methods and workflows I Mayer, A Sportisse, J Josse, N Tierney, N Vialaneix arXiv preprint arXiv:1908.04822, 2019 | 26 | 2019 |
| Debiasing averaged stochastic gradient descent to handle missing values A Sportisse, C Boyer, A Dieuleveut, J Josse Advances in Neural Information Processing Systems 33, 12957-12967, 2020 | 11 | 2020 |
| Robust Lasso‐Zero for sparse corruption and model selection with missing covariates P Descloux, C Boyer, J Josse, A Sportisse, S Sardy Scandinavian Journal of Statistics 49 (4), 1605-1635, 2022 | 9 | 2022 |
| Model-based clustering with missing not at random data A Sportisse, M Marbac, F Laporte, G Celeux, C Boyer, J Josse, ... arXiv preprint arXiv:2112.10425, 2021 | 6 | 2021 |
| Handling heterogeneous and MNAR missing data in statistical learning frameworks: imputation based on low-rank models, online linear regression with SGD, and model-based clustering A Sportisse Sorbonne université, 2021 | 3 | 2021 |
| Are labels informative in semi-supervised learning? Estimating and leveraging the missing-data mechanism. A Sportisse, H Schmutz, O Humbert, C Bouveyron, PA Mattei International Conference on Machine Learning, 32521-32539, 2023 | 2 | 2023 |
| Fed-MIWAE: Federated Imputation of Incomplete Data via Deep Generative Models I Balelli, A Sportisse, F Cremonesi, PA Mattei, M Lorenzi arXiv preprint arXiv:2304.08054, 2023 | 2 | 2023 |
| Debiasing Stochastic Gradient Descent to handle missing values J Josse, A Sportisse, C Boyer, A Dieuleveut arXiv preprint arXiv:2002.09338, 2020 | 2 | 2020 |
| Handling missing values J Josse, W Jiang, A Sportisse, G Robin Inria. Julie Josse. Retrieved October 12, 2020, 2018 | 2 | 2018 |
| Accompanying note: Model-based Clustering with Missing Not At Random Data A Sportisse, M Marbac, F Laporte, G Celeux, C Boyer, C Biernacki, ... | | 2023 |
| Impact of Missing Data on Mixtures and Clustering C Biernacki CMStatistics 2022-15th International Conference of the ERCIM WG on …, 2022 | | 2022 |
| Dealing with missing data in model-based clustering through a MNAR model C Biernacki, C Boyer, G Celeux, J Josse, F Laporte, MM Lourdelle, ... The 14th Professor Aleksander Zeliaś International Conference on Modelling …, 2021 | | 2021 |
| Estimation with informative missing data in the low-rank model with random effects A Sportisse, C Boyer, J Josse HAL 2019, 2019 | | 2019 |
| Bienvenue sur le portail HAL Paris Dauphine-PSL A Sportisse, M Marbac, C Biernacki, C Boyer, G Celeux | | |
| Dealing with missing data in model-based clustering through a MNAR model A Sportisse, C Biernacki, C Boyer, G Celeux, J Josse, F Laporte, ... | | |
| Estimation and imputation in PPCA models with Missing Not At Random Data A Sportisse, C Boyer, J Josse | | |
| Estimation avec des données incompletes informatives dans un cas de faible rang A Sportisse, C Boyer, J Josse | | |
| Low rank estimation with non-ignorable missing data C Boyer, J Josse, A Sportisse | | |
