Distributionally Robust and Multi-Objective Nonnegative Matrix Factorization

Nonnegative matrix factorization (NMF) is a linear dimensionality reduction technique for analyzing nonnegative data. A key aspect of NMF is the choice of the objective function that depends on the noise model (or statistics of the noise) assumed on the data. In many applications, the noise model is...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	IEEE transactions on pattern analysis and machine intelligence 2022-08, Vol.44 (8), p.4052-4064
Hauptverfasser:	Gillis, Nicolas, Hien, Le Thi Khanh, Leplat, Valentin, Tan, Vincent Y. F.
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Audio data Data models Dimensionality reduction distributional robustness Factorization Image reconstruction Linear programming Minimization multiple objectives multiplicative updates Nonnegative matrix factorization Optimization Robustness
Online-Zugang:	Volltext bestellen
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!