The increasing diversity of scientific and engineering data has driven the development of flexible techniques for inferring probability distributions without assuming a specific parametric family.

The calculation of nonparametric quantile regression curve estimates is often computationally intensive, as typically an expensive nonlinear optimization problem is involved. This article proposes a ...

Across modern data-intensive disciplines, the union of numerical computation, statistics, and machine learning has become ...