Converged Algorithms for Orthogonal Nonnegative Matrix Factorizations

2010/10/26 by Andri Mirzal, Mirzal, Andri · 1 citation
Computer Science · #Blind Source Separation Techniques #FOS: Computer and information sciences #FOS: Mathematics #Face and Expression Recognition #Machine Learning (cs.LG) #Matrix Theory and Algorithms #Numerical Analysis (math.NA)

paper · pdf · doi:10.48550/arxiv.1010.5290

openalex publication_date 2010/10/26 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

This paper proposes uni-orthogonal and bi-orthogonal nonnegative matrix factorization algorithms with robust convergence proofs. We design the algorithms based on the work of Lee and Seung [1], and derive the converged versions by utilizing ideas from the work of Lin [2]. The experimental results confirm the theoretical guarantees of the convergences.

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• A Convergent Algorithm for Bi-orthogonal Nonnegative Matrix Tri-Factorization

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