Gaussian Mixture Reduction With Composite Transportation Divergence

Gaussian mixtures are widely used for approximating density functions in various applications such as density estimation, belief propagation, and Bayesian filtering. These applications often utilize Gaussian mixtures as initial approximations that are updated recursively. A key challenge in these re...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	IEEE transactions on information theory 2024-07, Vol.70 (7), p.5191-5212
Hauptverfasser:	Zhang, Qiong, Zhang, Archer Gong, Chen, Jiahua
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Approximate inference Approximation belief propagation Clustering Clustering algorithms Computational efficiency Convergence Cost function Density density approximation Density functional theory Divergence Gaussian mixture reduction Mixture models Mixtures optimal transportation Optimization Transportation
Online-Zugang:	Volltext bestellen
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!