Norm-Based Generalization Bounds for Compositionally Sparse Neural Network
In this paper, we investigate the Rademacher complexity of deep sparse neural networks, where each neuron receives a small number of inputs. We prove generalization bounds for multilayered sparse ReLU neural networks, including convolutional neural networks. These bounds differ from previous ones, a...
| Main Authors: | , , , |
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| Format: | Article |
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Center for Brains, Minds and Machines (CBMM)
2023
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| Online Access: | https://hdl.handle.net/1721.1/148230 |