Abstract: We consider computing the QR factorization with column pivoting (QRCP) for a tall and skinny matrix, which has important applications including low-rank approximation and rank determination.

===== Benchmarks for 3×3 Float64 matrices ===== Matrix multiplication -> 5.9x speedup Matrix multiplication (mutating) -> 1.8x speedup Matrix addition -> 33.1x ...

Abstract: Dimension reduction is a critical data preprocessing step for many database and data mining applications, such as efficient storage and retrieval of high-dimensional data. In the literature, ...

In recent years, a learning method for classifiers using tensor networks (TNs) has attracted attention. When constructing a classification function for high-dimensional data using a basis function ...

Key Laboratory of Precision and Intelligent Chemistry, Department of Chemical Physics and Anhui Center for Applied Mathematics, University of Science and Technology of China, Hefei, Anhui 230026, ...

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 ...

In this project it is used a Machine Learning model based on a method called Extreme Learning, with the employment of L2-regularization. In particular, a comparison was carried out between: (A1) which ...

This paper concerns the more foundational tasks of distributed dense linear algebra. While a single TPU core can already store and operate on large matrices (e.g., of size 16,384, 32,768 in single ...

As artificial intelligence (AI) applications become ubiquitous in medical care, autonomous driving, robotics, and other fields, accuracy requirements and neural network complexity increase in tandem, ...