7 citations · 8 across the 3 of their papers we have counts for
3 papers
math.ST2024
Random features models: a way to study the success of naive imputation
Alexis Ayme, Claire Boyer, Aymeric Dieuleveut +1
Constant (naive) imputation is still widely used in practice as this is a first easy-to-use technique to deal with missing data. Yet, this simple method could be expected to induce…
math.ST2023★ 1 cited
Naive imputation implicitly regularizes high-dimensional linear models
Alexis Ayme, Claire Boyer, Aymeric Dieuleveut +1
Two different approaches exist to handle missing values for prediction: either imputation, prior to fitting any predictive algorithms, or dedicated methods able to natively incorpo…
math.ST2014★ 7 cited
On the asymptotics of random forests
Erwan Scornet
The last decade has witnessed a growing interest in random forest models which are recognized to exhibit good practical performance, especially in high-dimensional settings. On the…