This paper considers the problem of selecting the most informative experiments x to get measures y for learning an inference model y = f(x). We propose a novel concept for active learning, transductive experiment design, to overcome the shortcomings of existing experiment design methods, e.g. insufficient exploration of available unmeasured data and poor scalability for large data sets. In-dept...