Author

Aurélien F. Bibaut

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Preprint Sep 2026

Adaptive inference for functionals of M-estimands

Reinforcement learning and contextual bandit algorithms have become increasingly common in sequential decision-making applications. When these methods are deployed in high-stakes domains, there is growing interest not only in learning effective policies, but also in conducting statistical inference for quantities learn...

James Leiner, Aurélien F. Bibaut, Nathan Kallus et al. · 0 citations

#machine learning Preprint Sep 2026

Scalable Multi-Task Inverse Reinforcement Learning

By learning transferable rewards, inverse reinforcement learning (IRL) enables counterfactual evaluation of agents under modified environments. Such transfer places strict requirements on coverage since target environments affect agents'state occupancy. We propose a multi-task IRL method that pools data across multiple...

Allen Tran, Jia Wan, Nathan Kallus et al. · 0 citations