Abstract: Sparse Matrix-Matrix Multiplication (SpMM) is a widely used algorithm in Machine Learning, particularly in the increasingly popular Graph Neural Networks (GNNs). SpMM is an essential ...

Former Georgia gubernatorial candidate Stacey Abrams appeared on CNN Tuesday and said the Trump administration is using the assassination of Turning Point USA founder Charlie Kirk as an "excuse for ...

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 ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of computing a matrix inverse using the Newton iteration algorithm. Compared to other algorithms, Newton ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator.

Expertise from Forbes Councils members, operated under license. Opinions expressed are those of the author. In the quest to transform organizations, leaders often champion bold visions: compelling ...

Abstract: Matrix-matrix multiplication (MM) of large matrices plays a crucial role in various applications, including machine learning. MM requires significant computational resources, but accessing ...

The Nature Index 2025 Research Leaders — previously known as Annual Tables — reveal the leading institutions and countries/territories in the natural and health sciences, according to their output in ...

This project focuses on lossless compression techniques optimizing space, time, and energy for multiplications between binary (or ternary) matrix formats and real-valued vectors.