Minimum error entropy criterion‐based randomised autoencoder

Minimum error entropy criterion‐based randomised autoencoder

Abstract The extreme learning machine‐based autoencoder (ELM‐AE) has attracted a lot of attention due to its fast learning speed and promising representation capability. However, the existing ELM‐AE algorithms only reconstruct the original input and generally ignore the probability distribution of t...

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Bibliographic Details
Main Authors: Rongzhi Ma, Tianlei Wang, Jiuwen Cao, Fang Dong
Format: Article
Language:English
Published: Wiley 2021-12-01
Series:Cognitive Computation and Systems
Subjects:
learning (artificial intelligence)
probability
minimum entropy methods
iterative methods
entropy
Gaussian noise
Online Access:https://doi.org/10.1049/ccs2.12030

Internet

https://doi.org/10.1049/ccs2.12030

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