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ORCIDAurélien Bibaut
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- affiliation: Netflix
- affiliation: University of California, Berkeley, Division of Biostatistics, Ca, USA
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Books and Theses
- 2021
[b1]Aurélien F. Bibaut:
Statistical methods for causal inference fromsequentially collected data and sequential decisionmaking. University of California, Berkeley, USA, 2021
Conference and Workshop Papers
- 2024
- [c7]Allen Tran, Aurélien Bibaut, Nathan Kallus:
Inferring the Long-Term Causal Effects of Long-Term Treatments from Short-Term Experiments. ICML 2024 - [c6]Aurélien Bibaut
, Winston Chou, Simon Ejdemyr, Nathan Kallus:
Learning the Covariance of Treatment Effects Across Many Weak Experiments. KDD 2024: 153-162 - 2021
- [c5]Aurélien Bibaut, Nathan Kallus, Maria Dimakopoulou, Antoine Chambaz, Mark J. van der Laan:
Risk Minimization from Adaptively Collected Data: Guarantees for Supervised and Policy Learning. NeurIPS 2021: 19261-19273 - [c4]Aurélien Bibaut, Maria Dimakopoulou, Nathan Kallus, Antoine Chambaz, Mark J. van der Laan:
Post-Contextual-Bandit Inference. NeurIPS 2021: 28548-28559 - 2020
- [c3]Aurélien Bibaut, Antoine Chambaz, Mark J. van der Laan:
Generalized Policy Elimination: an efficient algorithm for Nonparametric Contextual Bandits. UAI 2020: 1099-1108 - 2019
- [c2]Aurélien Bibaut, Ivana Malenica, Nikos Vlassis, Mark J. van der Laan:
More Efficient Off-Policy Evaluation through Regularized Targeted Learning. ICML 2019: 654-663 - [c1]Nikos Vlassis, Aurélien Bibaut, Maria Dimakopoulou, Tony Jebara:
On the Design of Estimators for Bandit Off-Policy Evaluation. ICML 2019: 6468-6476
Informal and Other Publications
- 2021
- [i7]Ivana Malenica, Aurélien Bibaut, Mark J. van der Laan:
Adaptive Sequential Design for a Single Time-Series. CoRR abs/2102.00102 (2021) - [i6]Aurélien Bibaut, Antoine Chambaz, Maria Dimakopoulou, Nathan Kallus, Mark J. van der Laan:
Post-Contextual-Bandit Inference. CoRR abs/2106.00418 (2021) - [i5]Aurélien Bibaut, Antoine Chambaz, Maria Dimakopoulou, Nathan Kallus, Mark J. van der Laan:
Risk Minimization from Adaptively Collected Data: Guarantees for Supervised and Policy Learning. CoRR abs/2106.01723 (2021) - 2020
- [i4]Aurélien F. Bibaut, Antoine Chambaz, Mark J. van der Laan:
Generalized Policy Elimination: an efficient algorithm for Nonparametric Contextual Bandits. CoRR abs/2003.02873 (2020) - [i3]Aurélien F. Bibaut, Antoine Chambaz, Mark J. van der Laan:
Rate-adaptive model selection over a collection of black-box contextual bandit algorithms. CoRR abs/2006.03632 (2020) - 2019
- [i2]Aurélien F. Bibaut, Ivana Malenica, Nikos Vlassis, Mark J. van der Laan:
More Efficient Off-Policy Evaluation through Regularized Targeted Learning. CoRR abs/1912.06292 (2019) - 2017
- [i1]Cheng Ju, Aurélien Bibaut, Mark J. van der Laan:
The Relative Performance of Ensemble Methods with Deep Convolutional Neural Networks for Image Classification. CoRR abs/1704.01664 (2017)
Coauthor Index
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