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Imputation and low-rank estimation with Missing Not At Random data |
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| Authors: | Sportisse Aude Boyer Claire Josse Julie |
| Affiliation: | 1.Laboratoire de Probabilités Statistique et Modélisation, Sorbonne Université, Paris, France ;2.Centre de Mathématiques Appliquées, Ecole Polytechnique, Palaiseau, France ;3.Département de Mathématiques et applications, Ecole Normale Supérieure, Paris, France ;4.XPOP, INRIA Saclay, Palaiseau, France ; |
| Abstract: | Statistics and Computing - Missing values challenge data analysis because many supervised and unsupervised learning methods cannot be applied directly to incomplete data. Matrix completion based on... |
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