Dozens of machine learning algorithms require computing the inverse of a matrix. Computing a matrix inverse is conceptually easy, but implementation is one of the most challenging tasks in numerical ...

Last year, onlookers observed a startling site on China’s Qiantang River: waves forming a grid-like pattern. Dubbed the “matrix tide,” this complex wave pattern was caused by the river’s famed tidal ...

Abstract.The full-rank LDL* decomposition of a polynomial Hermitian matrix is examined. Explicit formulae are given evaluating the coefficients of matrices 𝑙𝑖𝑗 and 𝑑𝑗𝑗. Also, a new method is ...

This is a preview. Log in through your library . Abstract It is shown that a bounded bi-infinite banded totally positive matrix $A$ is boundedly invertible iff there ...

The challenge of speeding up AI systems typically means adding more processing elements and pruning the algorithms, but those approaches aren’t the only path forward. Almost all commercial machine ...

Up until now, the simulation hypothesis, which has occasionally received backing from the likes of Elon Musk and Neil deGrasse Tyson, was deemed to be un-testable in philosophy and science and often ...

Python is convenient and flexible, yet notably slower than other languages for raw computational speed. The Python ecosystem has compensated with tools that make crunching numbers at scale in Python ...

Over the last few issues, we've been talking about the math entity called a matrix. I've given examples of how matrices are useful and how matrix algebra can simplify complicated problems. A messy ...