基本信息
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职业迁徙
个人简介
My research work focuses on statistical learning, in particular on non-parametric algorithms such as random forests. This class of algorithms exhibits good accuracy in practice but theoretical results do not entirely explain their good empirical performances. Therefore random forests theory is very exciting. I am also interested in the notion of explainable AI and in particular how to provide insights about how the algorithm works. I am also working on connections between random forests and neural networks, which are also non-parametric algorithms with tremendous empirical performance.
More recently, I have started to work on missing value theory, trying to design algorithms that can
easily handle this type of data
More recently, I have started to work on missing value theory, trying to design algorithms that can
easily handle this type of data
研究兴趣
论文共 46 篇作者统计合作学者相似作者
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Annales de l'I.H.Pno. 1 (2023)
引用2浏览0引用
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arxiv(2023)
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0
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arXiv (Cornell University) (2023)
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Interpretability for Industry 4.0 : Statistical and Machine Learning Approachespp.37-84, (2022)
HAL (Le Centre pour la Communication Scientifique Directe) (2022)
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ICML 2022 (2022)
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arXiv (Cornell University) (2022)
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