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Analyzing the tree-layer structure of Deep Forests

 Ludovic Arnould , Claire Boyer , Erwan Scornet , Sorbonne Lpsm
International Conference on Machine Learning (ICML), Jul 2021, online, France
Communication dans un congrès hal-02974199v4
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Reweighting the RCT for generalization: finite sample error and variable selection

 Bénédicte Colnet , Julie Josse , Gaël Varoquaux , Erwan Scornet
2022
Pré-publication, Document de travail hal-03822662v2
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MDA for random forests: inconsistency, and a practical solution via the Sobol-MDA

 Clément Bénard , Sébastien da Veiga , Erwan Scornet
Biometrika, 2022, 109, pp.881-900
Article dans une revue hal-03151611v3
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Theoretical and experimental study of SMOTE: limitations and comparisons of rebalancing strategies

 Abdoulaye Sakho , Erwan Scornet , Emmanuel Malherbe
2024
Pré-publication, Document de travail hal-04438941v1
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Random features models: a way to study the success of naive imputation

 Alexis Ayme , Claire Boyer , Aymeric Dieuleveut , Erwan Scornet
2024
Pré-publication, Document de travail hal-04440304v1

A random forest guided tour (with comments and a rejoinder by the authors)

 Gérard Biau , Erwan Scornet
Test, 2016, 25, pp.197-227
Article dans une revue hal-01361796v1

A random forest guided tour

 Gérard Biau , Erwan Scornet
Test, 2016, pp.1-31. ⟨10.1007/s11749-016-0481-7⟩
Article dans une revue hal-01307105v1

AMF: Aggregated Mondrian Forests for Online Learning

 Jaouad Mourtada , Stéphane Gaïffas , Erwan Scornet
2020
Pré-publication, Document de travail hal-02976420v1

Minimax optimal rates for Mondrian trees and forests

 Jaouad Mourtada , Stéphane Gaïffas , Erwan Scornet
Annals of Statistics, 2020, 48 (4), pp.2253-2276. ⟨10.1214/19-AOS1886⟩
Article dans une revue hal-02976286v1

Random Forests and Kernel Methods

 Erwan Scornet
IEEE Transactions on Information Theory, 2016, PP (99), pp.1-1. ⟨10.1109/TIT.2016.2514489⟩
Article dans une revue hal-01255002v1
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Neural Random Forests

 Gérard Biau , Erwan Scornet , Johannes Welbl
Sankhya A, 2019
Article dans une revue hal-01306340v2
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Linear predictor on linearly-generated data with missing values: non consistency and solutions

 Marine Le Morvan , Nicolas Prost , Julie Josse , Erwan Scornet , Gaël Varoquaux
AISTATS 2020 - International Conference on Artificial Intelligence and Statistics, Aug 2020, Online, France. pp.3165-3174
Communication dans un congrès hal-02464569v2
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SIRUS: Stable and Interpretable RUle Set for Classification

 Clément Bénard , Gérard Biau , Sébastien da Veiga , Erwan Scornet
Electronic Journal of Statistics , 2021, 15, pp.427 - 505
Article dans une revue hal-02190689v4
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On the asymptotics of random forests

 Erwan Scornet
2014
Pré-publication, Document de travail hal-01061506v1
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Interpretable Random Forests via Rule Extraction

 Clément Bénard , Gérard Biau , Sébastien da Veiga , Erwan Scornet
Proceedings of The 24th International Conference on Artificial Intelligence and Statistics, 130, pp.937-945, 2021
Proceedings/Recueil des communications hal-02557113v4
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