MM-algorithms for traditional and convex NMF with Tweedie and Negative Binomial cost functions and empirical evaluation

ArXi:2603.09601v1 Announce Type: new Non-negative matrix factorisation (NMF) is a widely used tool for unsupervised learning and feature extraction, with applications ranging from genomics to text analysis and signal processing. Standard formulations of NMF are typically derived under Gaussian or Poisson noise assumptions, which may be inadequate for data exhibiting overdispersion or other complex mean-variance relationships.