15 citations · 22 across the 8 of their papers we have counts for
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math.ST2020★ 1 cited
Debiasing Stochastic Gradient Descent to handle missing values
Julie Josse, Aude Sportisse, Claire Boyer +1
Stochastic gradient algorithm is a key ingredient of many machine learning methods, particularly appropriate for large-scale learning.However, a major caveat of large data is their…
math.ST2019★ 15 cited
Estimation and imputation in Probabilistic Principal Component Analysis with Missing Not At Random data
Aude Sportisse, Claire Boyer, Julie Josse
Missing Not At Random (MNAR) values lead to significant biases in the data, since the probability of missingness depends on the unobserved values.They are ''not ignorable'' in the…