2 papers
stat.ML2026
PFN-TS: Thompson Sampling for Contextual Bandits via Prior-Data Fitted Networks
Yan Shuo Tan, Kenyon Ng, Ruizhe Deng +3
Thompson sampling is a widely used strategy for contextual bandits: at each round, it samples a reward function from a Bayesian posterior and acts greedily under that sample. Prior…
stat.ML2026
BFTS: Thompson Sampling with Bayesian Additive Regression Trees
Ruizhe Deng, Bibhas Chakraborty, Ran Chen +1
Contextual bandits are a core technology for personalized mobile health interventions, where decision-making requires adapting to complex, non-linear user behaviors. While Thompson…