Computing the inverse of a matrix is one of the most important operations in machine learning. If some matrix A has shape n-by-n, then its inverse matrix Ai is n-by-n and the matrix product of Ai * A ...

Uses matrix operations to process multiple SNP-gene pairs in parallel, known as sliced data processing Is able to perform ultra-fast eQTL analysis without loss of precision Can incorporate covariates, ...

In this page, we introduce a differential based method for vector and matrix derivatives (matrix calculus), which only needs a few simple rules to derive most matrix derivatives. This method is useful ...

Abstract: Matrix computation is ubiquitous in modern scientific and engineering fields. Due to the high computational complexity in conventional digital computers, matrix computation represents a ...