Before revision:  Along the way, we propose distributional optimal design , a natural extension of the optimal experiment design, and provide a sample-efficient learning algorithm for the problem, which may be of independent interest.
After revision:  Along the way, we propose distributional optimal design , a natural extension of the optimal experiment design, and provide a both statistically and computationally efficient learning algorithm for the problem, which may be of independent interest.