Reinforcement learning in large, structured action spaces: A simulation study of decision support for spinal cord injury rehabilitation. - Nathan Phelps; Stephanie Marrocco; Stephanie Cornell; Dalton L. Wolfe; Daniel J. Lizotte (CoRR, 2023)

Using Platt's scaling for calibration after undersampling - limitations and how to address them. - Nathan Phelps; Daniel J. Lizotte; Douglas G. Woolford (CoRR, 2024)

Challenges learning from imbalanced data using tree-based models: Prevalence estimates systematically depend on hyperparameters and can be upwardly biased. - Nathan Phelps; Daniel J. Lizotte; Douglas G. Woolford (CoRR, 2024)

Enhancing an existing algorithm for small-cardinality constrained portfolio optimisation. - Nathan Phelps; Adam Metzler (J. Oper. Res. Soc., 2024)

Towards understanding the bias in decision trees. - Nathan Phelps; Daniel J. Lizotte; Douglas G. Woolford (CoRR, 2025)