Matrix factorization algorithms help track neuronal activity They then excited the beads using blue laser light and collected the resulting fluorescence speckles using first a microscope objective and ...

High-performance matrix multiplication remains a cornerstone of numerical computing, underpinning a wide array of applications from scientific simulations to machine learning. Researchers ...

A new research paper titled “Discovering faster matrix multiplication algorithms with reinforcement learning” was published by researchers at DeepMind. “Here we report a deep reinforcement learning ...

Matrix computations are both fundamental and ubiquitous in computational science and its vast application areas. Along with the development of more advanced computer systems with complex memory ...

A new algorithm for reducing the bandwidth and profile of a sparse matrix is described. Extensive testing on finite element matrices indicates that the algorithm typically produces bandwidth and ...

A new paper develops a structured tool to evaluate the challenges surrounding artificial intelligence's accountability and ...

It utilizes advanced adaptive algorithms, aiming to redefine mathematics instruction and impact students, teachers, and parents.