Scientists at the California Institute of Technology have devised an AI-based approach to accelerate computations of quantum ...

SAN FRANCISCO — AccelChip Inc. has added a singular value decomposition (SVD) core generator to its AccelWare Advanced Math Toolkit to ease and speed implementation of sensor array processing ...

Parallel algorithms for singular value decomposition (SVD) have risen to prominence as an indispensable tool in high-performance numerical linear algebra. They offer significant improvements in the ...

Principal component analysis (PCA) is a classical machine learning technique. The goal of PCA is to transform a dataset into one with fewer columns. This is called dimensionality reduction. The ...

Caltech scientists have developed an artificial intelligence (AI)-based method that dramatically speeds up calculations of the quantum interactions ...

We describe the use of singular value decomposition in transforming genome-wide expression data from genes × arrays space to reduced diagonalized "eigengenes" × "eigenarrays" space, where the ...

Principal Component Analysis from Scratch Using Singular Value Decomposition with C# Dr. James McCaffrey of Microsoft Research presents a full-code, step-by-step tutorial on a classical ML technique ...