11 citations · 13 across the 4 of their papers we have counts for
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stat.ML2023★ 1 cited
Are labels informative in semi-supervised learning? -- Estimating and leveraging the missing-data mechanism
Aude Sportisse, Hugo Schmutz, Olivier Humbert +2
Semi-supervised learning is a powerful technique for leveraging unlabeled data to improve machine learning models, but it can be affected by the presence of ``informative'' labels,…
stat.ML2022★ 1 cited
Don't fear the unlabelled: safe semi-supervised learning via simple debiasing
Hugo Schmutz, Olivier Humbert, Pierre-Alexandre Mattei
Semi-supervised learning (SSL) provides an effective means of leveraging unlabelled data to improve a model performance. Even though the domain has received a considerable amount o…