Large-scale Machine Learning (ML) algorithms are often iterative, using repeated read-only data access and I/O-bound matrix-vector multiplications. Hence, it is crucial for performance to fit the data ...

Linear algebra operations are at the core of machine learning. Multiple specialized systems have emerged for the scalable, distributed execution of matrix and vector operations. The relationship of ...

Abstract: Sparse tensor algebra is widely used in many applications, including scientific computing, machine learning, and data analytics. The performance of sparse tensor algebra kernels strongly ...

Abstract: Clifford Algebra (CA) is a powerful mathematical language that allows for a simple and intuitive representation of geometric objects and their transformations. It has important applications ...

Data Science relies heavily on Linear Algebra. NumPy offers array-like data structures & dedicated operations and methods for Linear Algebra. NumPy is an essential Python library to perform ...

The Linear Algebra Calculator is a command-line utility that performs various matrix operations, such as addition, subtraction, determinant, row reduction, eigenvalue/eigenvector, etc. It is up to the ...

A calculator to perform boolean algebra operations and simplifications element-wise on matrices. Built with Common Lisp, and compiled with CLISP 2.49.60+. For example ...