GitHub

Comparative Study of Inference Methods for Bayesian Nonnegative Matrix Factorisation

This project contains an implementation of the Bayesian non-negative matrix factorisation and tri-factorisation models presented in the paper Comparative Study of Inference Methods for Bayesian ...
Frontiers

A Deep Non-negative Matrix Factorization Model for Big Data Representation Learning

Nowadays, deep representations have been attracting much attention owing to the great performance in various tasks. However, the interpretability of deep representations poses a vast challenge on real ...
GitHub

NMFLibrary: Non-negative Matrix Factorization Library

NMF solvers written by MATLAB, appplication MATLAB flies using NMF solvers, and your comments and suggestions. C.-J. Lin, "On the convergence of multiplicative update algorithms for nonnegative matrix ...
IEEE

Robust L/sub 1/ norm factorization in the presence of outliers and missing data by alternative convex programming

Abstract: Matrix factorization has many applications in computer vision. Singular value decomposition (SVD) is the standard algorithm for factorization. When there are outliers and missing data, which ...
IEEE

Unstructured Pruning and Low Rank Factorisation of Self-Supervised Pre-Trained Speech Models

Abstract: Self-supervised pre-trained speech models require significant memory and computational resources, limiting their applicability to many speech tasks. Unstructured pruning is a compression ...