Fast and Accurate Least-Mean-Squares Solvers

Alaa Maalouf, Ibrahim Jubran, Dan Feldman

Neural Information Processing Systems 

Least-mean squares (LMS) solvers such as Linear / Ridge / Lasso-Regression, SVD and Elastic-Net not only solve fundamental machine learning problems, but are also the building blocks in a variety of other methods, such as decision trees and matrix factorizations. We suggest an algorithm that gets a finite set of n d-dimensional real vectors and returns a weighted subset of d + 1 vectors whose sum is exactly the same. The proof in Caratheodory's Theorem (1907) computes such a subset in O(n