1 citations · 2 across the 4 of their papers we have counts for
4 papers
Games of Knightian Uncertainty as AGI testbeds
Spyridon Samothrakis, Dennis J. N. J. Soemers, Damian Machlanski
Arguably, for the latter part of the late 20th and early 21st centuries, games have been seen as the drosophila of AI. Games are a set of exciting testbeds, whose solutions (in ter…
Robustness of Algorithms for Causal Structure Learning to Hyperparameter Choice
Damian Machlanski, Spyridon Samothrakis, Paul Clarke
Hyperparameters play a critical role in machine learning. Hyperparameter tuning can make the difference between state-of-the-art and poor prediction performance for any algorithm,…
The Challenges of Hyperparameter Tuning for Accurate Causal Effect Estimation
Damian Machlanski, Spyridon Samothrakis, Paul Clarke
ML is playing an increasingly crucial role in estimating causal effects of treatments on outcomes from observational data. Many ML methods (`causal estimators') have been proposed…
Undersmoothing Causal Estimators with Generative Trees
Damian Machlanski, Spyros Samothrakis, Paul Clarke
Inferring individualised treatment effects from observational data can unlock the potential for targeted interventions. It is, however, hard to infer these effects from observation…