A Computational Framework for Multivariate Convex Regression and Its Variants
A Computational Framework for Multivariate Convex Regression and Its Variants
We study the nonparametric least squares estimator (LSE) of a multivariate convex regression function. The LSE, given as the solution to a quadratic program with O(n2) linear constraints (n being the sample size), is difficult to compute for large problems. Exploiting problem specific structure, we propose a scalable algorithmic framework …