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...

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Bibliographic Details

Published in:	IEEE signal processing letters Vol. 27; pp. 231 - 235
Main Authors:	Lim, Kart-Leong, Jiang, Xudong, Yi, Chenyu
Format:	Journal Article
Language:	English
Published:	New York IEEE 2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	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 Access:	Get full text
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