1 citations · 2 across the 2 of their papers we have counts for
2 papers
econ.EM2024★ 1 cited
Bandit Algorithms for Policy Learning: Methods, Implementation, and Welfare-performance
Toru Kitagawa, Jeff Rowley
Static supervised learning-in which experimental data serves as a training sample for the estimation of an optimal treatment assignment policy-is a commonly assumed framework of po…
cs.LG2024★ 1 cited
Adaptive Experimental Design for Policy Learning
Masahiro Kato, Kyohei Okumura, Takuya Ishihara +1
This study investigates the contextual best arm identification (BAI) problem, aiming to design an adaptive experiment to identify the best treatment arm conditioned on contextual i…