Non--negative matrix factorization using the R package

arXiv:2607.20084 · stat.ML, cs.LG · Submitted 2026-07-22 · Read on arXiv

Volkan Sevinç, Nikolas Kontemeniotis, Theodoros Perdikis, Michail Tsagris

stat.ML, cs.LG

Submitted: 2026-07-22

Code: https://github.com/zdebruine/RcppML

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Clustering — 9× in this paper · explained in 2 episodes
• Computational Efficiency — 7× in this paper · explained in 2 episodes
• Accuracy — 5× in this paper · explained in 1 episode
• Dimensionality Reduction — 5× in this paper · explained in 2 episodes
• Interpretability — 5× in this paper · explained in 15 episodes
• Reconstruction Error — 4× in this paper · explained in 2 episodes
• Benchmarking — 2× in this paper · explained in 4 episodes
• Comprehensive R Archive Network — 2× in this paper
• Feature Extraction — 2× in this paper · explained in 3 episodes
• Feature Selection — 2× in this paper · explained in 4 episodes
• Objective Function — 2× in this paper · explained in 2 episodes
• Robustness — 2× in this paper · explained in 6 episodes
• Adam — 1× in this paper · explained in 3 episodes
• Computational Biology — 1× in this paper · explained in 2 episodes
• Core — 1× in this paper · explained in 2 episodes
• Generalization — 1× in this paper · explained in 14 episodes
• K-means Clustering — 1× in this paper · explained in 3 episodes
• Kullback–Leibler Divergence — 1× in this paper · explained in 2 episodes
• Latent Representation — 1× in this paper · explained in 2 episodes
• Latent Representations — 1× in this paper · explained in 3 episodes
• Modular Architecture — 1× in this paper · explained in 4 episodes
• Predictive Modeling — 1× in this paper · explained in 3 episodes
• Quadratic Programming (QP) — 1× in this paper · explained in 3 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Sparsity — 1× in this paper · explained in 5 episodes

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