Fisher-rao metric, geometry, and complexity of neural networks
© 2019 by the author(s). We study the relationship between geometry and capacity measures for deep neural networks from an invariance viewpoint. We introduce a new notion of capacity - the Fisher-Rao norm - that possesses desirable invariance properties and is motivated by Information Geometry. We d...
Main Authors: | Liang, T (Author), Poggio, T (Author), Rakhlin, A (Author), Stokes, J (Author) |
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Format: | Article |
Language: | English |
Published: |
2021-12-02T20:14:53Z.
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Subjects: | |
Online Access: | Get fulltext |
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