Information Theoretic Learning Renyi's Entropy and Kernel Perspectives /
This book presents the first cohesive treatment of Information Theoretic Learning (ITL) algorithms to adapt linear or nonlinear learning machines both in supervised or unsupervised paradigms. ITL is a framework where the conventional concepts of second order statistics (covariance, L2 distances, cor...
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| Format: | Electronic |
| Language: | English |
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New York, NY :
Springer New York : Imprint: Springer,
2010.
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| Series: | Information Science and Statistics,
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| Online Access: | https://ezaccess.library.uitm.edu.my/login?url=http://dx.doi.org/10.1007/978-1-4419-1570-2 |