In this paper we develop an online platform for preference elicitation where users report their preferences between alternatives over a moderate number of pairwise comparisons chosen by a particular elicitation procedure.

This paper derives consistency rates for random forests, as they are used in practice, in a general high-dimensional nonparametric regression setting. Our new theoretical results show that random forests can indeed adapt to high dimensionality and allow for discontinuous regression function.

This paper provide an in-depth technical analysis of the distribution nearest neighbors (DNN) method, based on which we suggest a bias reduction approach for the DNN estimator by linearly combining two DNN estimators with different subsampling scales, resulting in the novel two-scale DNN (TDNN) estimator.

In this paper, we develop a theory of intersectional substantive representation of and by immigrant communities grounded in two concepts: representational orientation to constituents and representational activity to achieve goals.