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Aurelien Bibaut
Aurelien Bibaut
Unknown affiliation
Verified email at berkeley.edu
Title
Cited by
Cited by
Year
The relative performance of ensemble methods with deep convolutional neural networks for image classification
C Ju, A Bibaut, M van der Laan
Journal of applied statistics 45 (15), 2800-2818, 2018
3812018
Fast rates for empirical risk minimization over cadlag functions with bounded sectional variation norm
AF Bibaut, MJ van der Laan
arXiv, arXiv: 1907.09244, 2019
402019
More efficient off-policy evaluation through regularized targeted learning
A Bibaut, I Malenica, N Vlassis, M Van Der Laan
International Conference on Machine Learning, 654-663, 2019
372019
Post-contextual-bandit inference
A Bibaut, M Dimakopoulou, N Kallus, A Chambaz, M van Der Laan
Advances in neural information processing systems 34, 28548-28559, 2021
342021
On the design of estimators for bandit off-policy evaluation
N Vlassis, A Bibaut, M Dimakopoulou, T Jebara
International Conference on Machine Learning, 6468-6476, 2019
292019
Finding hotspots: development of an adaptive spatial sampling approach
R Andrade-Pacheco, F Rerolle, J Lemoine, L Hernandez, A Meïté, ...
Scientific reports 10 (1), 10939, 2020
232020
Risk minimization from adaptively collected data: Guarantees for supervised and policy learning
A Bibaut, N Kallus, M Dimakopoulou, A Chambaz, M van Der Laan
Advances in neural information processing systems 34, 19261-19273, 2021
152021
CV-TMLE for nonpathwise differentiable target parameters
MJ van der Laan, S Rose, MJ van der Laan, A Bibaut, AR Luedtke
Targeted Learning in Data Science: Causal Inference for Complex Longitudinal …, 2018
142018
Uniform consistency of the highly adaptive lasso estimator of infinite dimensional parameters
MJ van der Laan, AF Bibaut
arXiv preprint arXiv:1709.06256, 2017
102017
Data-adaptive smoothing for optimal-rate estimation of possibly non-regular parameters
AF Bibaut, MJ van der Laan
arXiv preprint arXiv:1706.07408, 2017
92017
Rate-adaptive model selection over a collection of black-box contextual bandit algorithms
AF Bibaut, A Chambaz, MJ van der Laan
arXiv preprint arXiv:2006.03632, 2020
82020
One-step ahead sequential Super Learning from short times series of many slightly dependent data, and anticipating the cost of natural disasters
G Ecoto, A Bibaut, A Chambaz
arXiv preprint arXiv:2107.13291, 2021
72021
Sequential causal inference in a single world of connected units
A Bibaut, M Petersen, N Vlassis, M Dimakopoulou, M van der Laan
arXiv preprint arXiv:2101.07380, 2021
72021
Near-optimal non-parametric sequential tests and confidence sequences with possibly dependent observations
A Bibaut, N Kallus, M Lindon
arXiv preprint arXiv:2212.14411, 2022
62022
Adaptive sequential design for a single time-series
I Malenica, A Bibaut, MJ van der Laan
arXiv preprint arXiv:2102.00102, 2021
52021
Sufficient and insufficient conditions for the stochastic convergence of Ces\{a} ro means
AF Bibaut, A Luedtke, MJ van der Laan
arXiv preprint arXiv:2009.05974, 2020
22020
Generalized Policy Elimination: an efficient algorithm for Nonparametric Contextual Bandits
AF Bibaut, A Chambaz, MJ van der Laan
Uncertainty in Artificial Intelligence 124, 1099-1108, 2020
22020
Learning the Covariance of Treatment Effects Across Many Weak Experiments
A Bibaut, W Chou, S Ejdemyr, N Kallus
arXiv preprint arXiv:2402.17637, 2024
2024
Inferring the Long-Term Causal Effects of Long-Term Treatments from Short-Term Experiments
A Tran, A Bibaut, N Kallus
arXiv preprint arXiv:2311.08527, 2023
2023
Long-Term Causal Inference with Imperfect Surrogates using Many Weak Experiments, Proxies, and Cross-Fold Moments
A Bibaut, N Kallus, S Ejdemyr, M Zhao
arXiv preprint arXiv:2311.04657, 2023
2023
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