3 citations · 3 across the 7 of their papers we have counts for
3 papers · 1 filter
Nash Equilibrium Individualized Treatment Regimes under Network Interference
Junwen Xia, Jingxiao Zhang, Dehan Kong
Network interference creates a fundamental tension in optimal individualized treatment regime learning: maximizing overall population outcomes may come at the expense of some indiv…
A Statistically Reliable Optimization Framework for Bandit Experiments in Scientific Discovery
Tong Li, Travis Mandel, Goldie Phillips +4
Scientific experimentation is largely driven by statistical hypothesis testing to determine significant differences in interventions. Traditionally, experimenters allocate samples…
RIE-Greedy: Regularization-Induced Exploration for Contextual Bandits
Tong Li, Thiago de Queiroz Casanova, Eric M. Schwartz +3
Real-world contextual bandit problems with complex reward models are often tackled with iteratively trained models, such as boosting trees. However, it is difficult to directly app…