Linear feature selection with applications

TL;DR: A multistage classification scheme is proposed which reduces the processing time substantially by eliminating unlikely classes from further consideration at each stage by exploiting the increased importance of the second order statistics in analyzing high dimensional data.

TL;DR: The purpose of this paper is to discuss the problem of finding a lower dimension q p which in some sense best fits the range space generated by the matrix M and provide a partial solution.

TL;DR: This book shows engineers how to use optimization theory to solve complex problems with a minimum of mathematics and unifies the large field of optimization with a few geometric principles.

TL;DR: A number of theorems are proved to show that it always converges and that it converges rapidly, and this method has been used to solve a system of one hundred non-linear simultaneous equations.