Learning the sparse prior: Modern approaches

The sparse prior has been widely adopted to establish data models for numerous applications. In this context, most of them are based on one of three foundational paradigms: the conventional sparse representation, the convolutional sparse representation, and the multi‐layer convolutional sparse repre...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	Wiley interdisciplinary reviews. Computational statistics Jg. 16; H. 1; S. e1646 - n/a
1. Verfasser:	Peng, Guan‐Ju
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Hoboken, USA John Wiley & Sons, Inc 01.01.2024 Wiley Subscription Services, Inc
Schlagworte:	algorithm unrolling Algorithms Coding convex and non‐convex optimization Convexity convolutional sparse model Data analysis Dictionaries dictionary learning Glossaries Graphical methods Learning Machine learning Modelling Morphology multi‐layer convolutional sparse model Neural networks Optimization recurrent neural network Recurrent neural networks Representations sparse coding sparse prior Supervised learning Training
ISSN:	1939-5108, 1939-0068
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!