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 ...

Dr. James McCaffrey of Microsoft Research presents a full-code, step-by-step tutorial on an implementation of the technique that emphasizes simplicity and ease-of-modification over robustness and ...

This is a preview. Log in through your library . Abstract ABSTRACT The author revisits the singular value decomposition (SVD) method and shows that the nonuniqueness of the left and right singular ...

Many multivariate data-analysis techniques for an m × n matrix Y are related to the model Y = M + E, where Y is an m × n matrix of full rank and M is an unobserved mean matrix of rank K < (m Λ n).

Caltech scientists have developed an artificial intelligence (AI)–based method that dramatically speeds up calculations of ...

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

The latest information from the National Intellectual Property Administration shows that Guogong Zhisoft (Nanjing) Information Technology Co., Ltd. applied for a patent in June 2025, titled "A Sample ...