The job title Quant is ubiquitously used. That makes it a dynamic, exciting and dynamic discipline, but one which also can ...

Introduction to linear algebra by Lang, Serge, 1927-2005. Publication date 1986 Topics Algebras, Linear Publisher New York : Springer-Verlag Collection internetarchivebooks; printdisabled Contributor ...

RandBLAS facilitates implementation of high-level randomized linear algebra algorithms, like randomized low-rank SVD. It does this by providing basic functionality for sketching with a BLAS-like ...

Compared with other problem book, this one has few new basic features. They include problems dealing with polynomial matrices (Sec. 13), linear transformations of affine and metric spaces (Secs. 18 ...

Machine learning and numerical simulation represent opposite approaches to computational analysis of the real world, inductive vs. deductive. However, both methods suffer from various uncertainties ...

A stand-alone pure Java library for linear algebra and machine learning. java machine-learning ... java vector matrix linear-algebra eigen singular-values tensor linear-algebra-library eigenvalue ...

Usually the version with combinatorial optimization and matrix theory, convexity and polyhedral theory, and also an introduction to polyhedral combinatorics. Learning outcome. ... MAT-INF1100 – ...

A mixed numerical and analytical analysis of oscillatory non-harmonic solutions of nonlinear circuits with nonsmooth inputs is presented. The focus of the paper is on using hyperbolic algebra in the ...