Linear least squares: minimize Ax - b 2 (1.2) where A is a matrix with m rows and n columns, b is an m-vectoris a scalar, and the given data A, b, ), are real. The matrix A will normally be large and sparse. It is deemed by means of a user-written subroutine APROD, whose. Over the past decades, Linear Programming (LP) has been widely used in. LP instances from l1-regularized multi-class SVM, Sparse Inverse Covariance Es.
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