Understanding neural network sample complexity and interpretable convergence-guaranteed deep learning with polynomial regression
Thesis: S.M., Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, May, 2020 === Cataloged from PDF version of thesis. === Includes bibliographical references (pages 83-89). === We first study the sample complexity of one-layer neural networks, namely the nu...
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| Format: | Others |
| Language: | English |
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Massachusetts Institute of Technology
2020
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| Online Access: | https://hdl.handle.net/1721.1/127290 |