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A Theory for Learning by Weight Flow on Stiefel-Grassman Manifold.

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Title: A Theory for Learning by Weight Flow on Stiefel-Grassman Manifold.
Authors: Fiori, Simone
Source: Neural Computation. Jul2001, Vol. 13 Issue 7, p1625-1647. 23p.
Subjects: Artificial neural networks, Stiefel manifolds
Abstract: Recently we introduced the concept of neural network learning on Stiefel-Grassman manifold for multilayer perceptron-like networks. Contributions of other authors have also appeared in the scientific literature about this topic. This article presents a general theory for it and illustrates how existing theories may be explained within the general framework proposed here. [ABSTRACT FROM AUTHOR]
Copyright of Neural Computation is the property of MIT Press and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: Recently we introduced the concept of neural network learning on Stiefel-Grassman manifold for multilayer perceptron-like networks. Contributions of other authors have also appeared in the scientific literature about this topic. This article presents a general theory for it and illustrates how existing theories may be explained within the general framework proposed here. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Neural Computation is the property of MIT Press and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – SubjectFull: Stiefel manifolds
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