Erwan Scornet
14 papers · 2017–2025 · 4 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
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🌉 Interdisciplinary Bridge · Silver 🗺️ Taxonomy Completionist (20) 🌍 Conference Polyglot · Bronze 🐣 Hot Topic Early Bird 🏃 Academic Marathon · Sprint
❓
The Questioner
(2)
🔥
Unstoppable · Bronze
💎
Century Club · Bronze
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Keyword Collector
(59)
Venues
Top co-authors
Research topics
Machine Learning
(12)
Core Methods
(12)
Optimization & Theory
(9)
Learning Types
(5)
Artificial Intelligence
(3)
Mathematics & Optimization
(2)
Core AI
(2)
Deep Learning
(1)
Healthcare & Medicine
(1)
Knowledge & Reasoning
(1)
Architectures
(1)
Clinical
(1)
Learning Paradigms
(1)
Mathematics
(1)
Reasoning
(1)
Keywords
random forest
(5)
missing data
(3)
decision tree
(3)
excess risk
(3)
neural network
(2)
missing value
(2)
supervised learning
(2)
ridge regression
(1)
linear discriminant analysis
(1)
online learning
(1)
neural network optimization
(1)
minimax estimation
(1)
differentiable programming
(1)
joint learning
(1)
logistic regression
(1)
missing value imputation
(1)
high-dimensional linear model
(1)
feature importance
(1)
variable importance
(1)
sparse feature extraction
(1)
Papers
A primer on linear classification with missing data
AISTATS 2025
Quantifying Treatment Effects: Estimating Risk Ratios via Observational Studies
ICML 2025
Random features models: a way to study the success of naive imputation
ICML 2024
Is interpolation benign for random forest regression?
AISTATS 2023
Naive imputation implicitly regularizes high-dimensional linear models
ICML 2023
Sparse tree-based Initialization for Neural Networks
ICLR 2023
Near-optimal rate of consistency for linear models with missing values
ICML 2022
SHAFF: Fast and consistent SHApley eFfect estimates via random Forests
AISTATS 2022
Analyzing the tree-layer structure of Deep Forests
ICML 2021
Interpretable Random Forests via Rule Extraction
AISTATS 2021
What’s a good imputation to predict with missing values?
NeurIPS 2021
Linear predictor on linearly-generated data with missing values: non consistency and solutions
AISTATS 2020
NeuMiss networks: differentiable programming for supervised learning with missing values.
NeurIPS 2020
Universal consistency and minimax rates for online Mondrian Forests
NeurIPS 2017