Erwan Scornet

According to our database1, Erwan Scornet authored at least 22 papers between 2016 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Links

On csauthors.net:

Bibliography

2024
Theoretical and experimental study of SMOTE: limitations and comparisons of rebalancing strategies.
CoRR, 2024

Random features models: a way to study the success of naive imputation.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023
Naive imputation implicitly regularizes high-dimensional linear models.
Proceedings of the International Conference on Machine Learning, 2023

Sparse tree-based Initialization for Neural Networks.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Is interpolation benign for random forest regression?
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022
Minimax rate of consistency for linear models with missing values.
CoRR, 2022

Near-optimal rate of consistency for linear models with missing values.
Proceedings of the International Conference on Machine Learning, 2022

SHAFF: Fast and consistent SHApley eFfect estimates via random Forests.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
MDA for random forests: inconsistency, and a practical solution via the Sobol-MDA.
CoRR, 2021

What's a good imputation to predict with missing values?
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Analyzing the tree-layer structure of Deep Forests.
Proceedings of the 38th International Conference on Machine Learning, 2021

Interpretable Random Forests via Rule Extraction.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
Neumann networks: differential programming for supervised learning with missing values.
CoRR, 2020

NeuMiss networks: differentiable programming for supervised learning with missing values.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Linear predictor on linearly-generated data with missing values: non consistency and solutions.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
SIRUS: making random forests interpretable.
CoRR, 2019

AMF: Aggregated Mondrian Forests for Online Learning.
CoRR, 2019

On the consistency of supervised learning with missing values.
CoRR, 2019

2017
Universal consistency and minimax rates for online Mondrian Forests.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016
Random Forests and Kernel Methods.
IEEE Trans. Inf. Theory, 2016

On the asymptotics of random forests.
J. Multivar. Anal., 2016

Neural Random Forests.
CoRR, 2016


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