Deep Clustering With Variational Autoencoder

An autoencoder that learns a latent space in an unsupervised manner has many applications in signal processing. However, the latent space of an autoencoder does not pursue the same clustering goal as Kmeans or GMM. A recent work proposes to artificially re-align each point in the latent space of an...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	IEEE signal processing letters Jg. 27; S. 231 - 235
Hauptverfasser:	Lim, Kart-Leong, Jiang, Xudong, Yi, Chenyu
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Bayes methods Clustering Datasets Energy management Euclidean geometry Gaussian distribution Optimization Photovoltaic cells Probabilistic logic Probabilistic models Probability distribution Random variables Signal processing Statistical analysis
ISSN:	1070-9908, 1558-2361
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!