On Generalization Bounds for Neural Networks with Low Rank Layers
While previous optimization results have suggested that deep neural networks tend to favour low-rank weight matrices, the implications of this inductive bias on generalization bounds remain under-explored. In this paper, we apply a chain rule for Gaussian complexity (Maurer, 2016a) to analyze how lo...
| Main Authors: | , , |
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| Format: | Article |
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Center for Brains, Minds and Machines (CBMM)
2024
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| Online Access: | https://hdl.handle.net/1721.1/157263 |