#ICYMI on the BGSE Data Science blog: RandNLA for LS (Part 2)

Randomized Numerical Linear Algebra for Least Squares – Part 2

by Robert Lange ’17

In today’s article we are going to introduce the Fast Johnson Lindenstrauss Transform (FJLT). This result is going to be the fundament of two very important concepts which speed up the computation of an ε-approximation to the LS objective function and the target vector…

See also Part 1 of this post