Algorithms have been used throughout the world’s civilizations to perform fundamental operations for thousands of years. However, discovering algorithms is highly challenging. Matrix multiplication is ...

Abstract: The fundamental building block of many algorithms such as data analytics and neural networks is matrix multiplication. Besides its popularity, matrix multiplication is one of the rare ...

Theorem. Currently it contains a (partial) statement of the Min-Max Theorem without proof, and a proof of the Cauchy Interlacing Theorem from that statement. *) From mathcomp Require Import ...

This PyTorch extension provides a drop-in replacement for torch.nn.Linear using block sparse matrices instead of dense ones. It enables very easy experimentation with sparse matrices since you can ...

Abstract: The authors give a criterion of nonsingular block H- matrices and introduce the concepts of block $\alpha$ - bidiagonally dominant matrices. A new criterion for block H-matrices is given.

For the large sparse block two-by-two real nonsingular matrices, we establish a general framework of practical and efficient structured preconditioners through matrix transformation and matrix ...

Matrix multiplication is a fundamental operation in linear algebra and has numerous applications in various fields of science, engineering, and computation. Multiplying matrices may seem complicated ...

Department of Cyber-Physical Systems, Clark Atlanta University, Atlanta, GA, USA. where P is some reflection (symmetric signed permutation) matrix. Like U, the generalized reflexive matrices A arise ...