IEEE

Physics-Informed Matrix Factorization Operator

Abstract: Matrix factorization is a fundamental characterization model in machine learning and is usually solved using mathematical decomposition reconstruction loss. However, matrix factorization is ...
IEEE

Machine Learning Source Separation Using Maximum a Posteriori Nonnegative Matrix Factorization

Abstract: A novel unsupervised machine learning algorithm for single channel source separation is presented. The proposed method is based on nonnegative matrix factorization, which is optimized under ...
eLife

Unsupervised detection of fragment length signatures of circulating tumor DNA using non-negative matrix factorization

Sequencing of cell-free DNA (cfDNA) is currently being used to detect cancer by searching both for mutational and non-mutational alterations. Recent work has shown that the length distribution of ...
Frontiers

Novel Collaborative Weighted Non-negative Matrix Factorization Improves Prediction of Disease-Associated Human Microbes

Extensive clinical and biomedical studies have shown that microbiome plays a prominent role in human health. Identifying potential microbe–disease associations (MDAs) can help reveal the pathological ...
GitHub

NTFk: Nonnegative Tensor Factorization using k-means clustering and physics constraints

NTFk is a module of the SmartTensors ML framework (smarttensors.com). NTFk performs a novel unsupervised Machine Learning (ML) method based on Tensor Decomposition (Factorization) coupled with ...
Searchenginejournal.com

How To Build A Recommender System With TF-IDF And NMF (Python)

Topic clusters and recommender systems can help SEO experts to build a scalable internal linking architecture. And as we know, internal linking can impact both user experience and search rankings.
GitHub

NMFk: Nonnegative Matrix Factorization + k-means clustering and physics constraints

NMFk is a module of the SmartTensors ML framework (smarttensors.com). NMFk is a novel unsupervised machine learning methodology that allows for the automatic identification of the optimal number of ...
Scientific Research Publishing

Unsupervised Multi-Level Non-Negative Matrix Factorization Model: Binary Data Case ()

Rank determination issue is one of the most significant issues in non-negative matrix factorization (NMF) research. However, rank determination problem has not received so much emphasis as sparseness ...