Publications

Toward Computationally Efficient Inverse Reinforcement Learning via Reward Shaping

Inverse reinforcement learning (IRL) is computationally challenging, with common approaches requiring the solution of multiple …

Lauren H. Cooke*, Harvey Klyne*, Edwin Zhang*, Cassidy Laidlaw, Milind Tambe, Finale Doshi-Velez

Toward Computationally Efficient Inverse Reinforcement Learning via Reward Shaping

Average partial effect estimation using double machine learning

Single-parameter summaries of variable effects are desirable for ease of interpretation, but linear models, which would deliver these, …

Harvey Klyne, Rajen D. Shah

Average partial effect estimation using double machine learning

Semiparametric Methods for Two Problems in Causal Inference using Machine Learning

Scientific applications such as personalised (precision) medicine require statistical guarantees on causal mechanisms, however in many …

Harvey Klyne

Semiparametric Methods for Two Problems in Causal Inference using Machine Learning