Where Does Minimum Error Entropy Outperform Minimum Mean Square Error? A New and Closer Look

Where Does Minimum Error Entropy Outperform Minimum Mean Square Error? A New and Closer Look

The past decade has seen a rapid application of information theoretic learning (ITL) criteria in robust signal processing and machine learning problems. Generally, in ITL's literature, it is seen that, under non-Gaussian assumptions, especially when the data are corrupted by heavy-tailed or mul...

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Podrobná bibliografie
Hlavní autoři: Ahmad Reza Heravi, Ghosheh Abed Hodtani
Médium: Článek
Jazyk:English
Vydáno: IEEE 2018-01-01
Edice:IEEE Access
Témata:
Entropy
mean square error methods
machine learning algorithms
information theoretic learning
Kullback-Leibler divergence
On-line přístup:https://ieeexplore.ieee.org/document/8264748/

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https://ieeexplore.ieee.org/document/8264748/

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