GitHub

LaFA: Latent Feature Attacks on Non-negative Matrix Factorization

As Machine Learning (ML) applications rapidly grow, concerns about adversarial attacks compromising their reliability have gained significant attention. One unsupervised ML method known for its ...
IEEE

Probabilistic Matrix Factorization Recommendation Approach for Integrating Multiple Information Sources

Abstract: Most previous studies on matrix factorization (MF)-based collaborative filtering (CF) have focused solely on user rating information for predicting recommendations. However, to further ...
IEEE

Semi-Supervised Symmetric Non-Negative Matrix Factorization With Low-Rank Tensor Representation

Abstract: Semi-supervised symmetric non-negative matrix factorization (SNMF) utilizes the available supervisory information (usually in the form of pairwise constraints) to improve the clustering ...