IEEE

Heuristic method for attribute reduction of concept lattice based on Boolean matrix

Abstract: The improved attribute reduction method based on Boolean matrix of rough set in Reference [6–9] transplanted to concept lattice field. Based on definition of Boolean matrix structural way ...
GitHub

A Python demonstration of speeding up matrix multiplication and reducing memory using a quantum-inspired low-rank SVD trick, with examples in AI.

This repository demonstrates a powerful, classical linear algebra technique—low-rank approximation via Singular Value Decomposition (SVD)—to dramatically accelerate common matrix operations like GEMM ...
Visual Studio Magazine

Computing the Determinant of a Matrix Using Gaussian Elimination to Row Echelon Form with C#

One of the fundamental operations in machine learning is computing the inverse of a square matrix. But not all matrices have an inverse. The most common way to check if a matrix has an inverse or not ...
University of Waterloo

Instance Ranking and Numerosity Reduction Using Matrix Decompositionand Subspace Learning

Ghojogh, B. & Crowley, M., 2019. Instance Ranking and Numerosity Reduction Using Matrix Decompositionand Subspace Learning. In Canadian Conference on Artificial Intelligence. Kingston, ON, Canada: ...
IEEE

GEVD Based Speech and Noise Correlation Matrix Estimation for Multichannel Wiener Filter Based Noise Reduction

Abstract: In a single speech source noise reduction scenario, the frequency domain correlation matrix of the speech signal is often assumed to be a rank-l matrix. In multichannel Wiener filter (MWF) ...
JSTOR Daily

Dimension Reduction in Regression without Matrix Inversion

This is a preview. Log in through your library . Abstract Regressions in which the fixed number of predictors p exceeds the number of independent observational units n occur in a variety of scientific ...