3 citations · 3 across the 2 of their papers we have counts for
3 papers
cs.LG2022
Variance-Optimal Augmentation Logging for Counterfactual Evaluation in Contextual Bandits
Aaron David Tucker, Thorsten Joachims
Methods for offline A/B testing and counterfactual learning are seeing rapid adoption in search and recommender systems, since they allow efficient reuse of existing log data. Howe…
cs.CY2020★ 3 cited
Social and Governance Implications of Improved Data Efficiency
Aaron D. Tucker, Markus Anderljung, Allan Dafoe
Many researchers work on improving the data efficiency of machine learning. What would happen if they succeed? This paper explores the social-economic impact of increased data effi…
cs.LG2018
Inverse reinforcement learning for video games
Aaron Tucker, Adam Gleave, Stuart Russell
Deep reinforcement learning achieves superhuman performance in a range of video game environments, but requires that a designer manually specify a reward function. It is often easi…