Aurélien Bibaut

19 papers A* 6A 1Journal 11Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Efficient Inference after Directionally Stable Adaptive Experiments. CoRR Zikai Shen, Houssam Zenati, Nathan Kallus, Arthur Gretton, Koulik Khamaru, Aurélien Bibaut
2025	J	`jnl`	Automatic Double Reinforcement Learning in Semiparametric Markov Decision Processes with Applications to Long-Term Causal Inference. CoRR Lars van der Laan, David Hubbard, Allen Tran, Nathan Kallus, Aurélien Bibaut
2025	J	`jnl`	Efficient Inference for Inverse Reinforcement Learning and Dynamic Discrete Choice Models. CoRR Lars van der Laan, Aurélien Bibaut, Nathan Kallus
2025	—	`conf`	Evaluating Decision Rules Across Many Weak Experiments. KDD (2) Winston Chou, Colin Gray, Nathan Kallus, Aurélien Bibaut, Simon Ejdemyr
2025	J	`jnl`	Inverse Reinforcement Learning Using Just Classification and a Few Regressions. CoRR Lars van der Laan, Nathan Kallus, Aurélien Bibaut
2025	J	`jnl`	Online Policy Learning via a Self-Normalized Maximal Inequality. CoRR Samuel Girard, Aurélien Bibaut, Houssam Zenati
2025	J	`jnl`	Simulation-Based Inference for Adaptive Experiments. CoRR Brian M. Cho, Aurélien Bibaut, Nathan Kallus
2025	J	`jnl`	The Value of Personalized Recommendations: Evidence from Netflix. CoRR Kevin Zielnicki, Guy Aridor, Aurélien Bibaut, Allen Tran, Winston Chou, Nathan Kallus
2024	A*	`conf`	Inferring the Long-Term Causal Effects of Long-Term Treatments from Short-Term Experiments. ICML Allen Tran, Aurélien Bibaut, Nathan Kallus
2024	A*	`conf`	Learning the Covariance of Treatment Effects Across Many Weak Experiments. KDD Aurélien Bibaut, Winston Chou, Simon Ejdemyr, Nathan Kallus
2021	J	`jnl`	Adaptive Sequential Design for a Single Time-Series. CoRR Ivana Malenica, Aurélien Bibaut, Mark J. van der Laan
2021	A*	`conf`	Post-Contextual-Bandit Inference. NeurIPS Aurélien Bibaut, Maria Dimakopoulou, Nathan Kallus, Antoine Chambaz, Mark J. van der Laan
2021	J	`jnl`	Post-Contextual-Bandit Inference. CoRR Aurélien Bibaut, Antoine Chambaz, Maria Dimakopoulou, Nathan Kallus, Mark J. van der Laan
2021	A*	`conf`	Risk Minimization from Adaptively Collected Data: Guarantees for Supervised and Policy Learning. NeurIPS Aurélien Bibaut, Nathan Kallus, Maria Dimakopoulou, Antoine Chambaz, Mark J. van der Laan
2021	J	`jnl`	Risk Minimization from Adaptively Collected Data: Guarantees for Supervised and Policy Learning. CoRR Aurélien Bibaut, Antoine Chambaz, Maria Dimakopoulou, Nathan Kallus, Mark J. van der Laan
2020	A	`conf`	Generalized Policy Elimination: an efficient algorithm for Nonparametric Contextual Bandits. UAI Aurélien Bibaut, Antoine Chambaz, Mark J. van der Laan
2019	A*	`conf`	More Efficient Off-Policy Evaluation through Regularized Targeted Learning. ICML Aurélien Bibaut, Ivana Malenica, Nikos Vlassis, Mark J. van der Laan
2019	A*	`conf`	On the Design of Estimators for Bandit Off-Policy Evaluation. ICML Nikos Vlassis, Aurélien Bibaut, Maria Dimakopoulou, Tony Jebara
2017	J	`jnl`	The Relative Performance of Ensemble Methods with Deep Convolutional Neural Networks for Image Classification. CoRR Cheng Ju, Aurélien Bibaut, Mark J. van der Laan