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About Deep Neural Networks Are Lazy: On The Inductive Bias of Deep Learning
This document is the thesis submitted by Tarek Mansour to the Department of Electrical Engineering and Computer Science at MIT in partial fulfillment of the requirements for a Master of Engineering degree. The thesis explores the inductive bias of deep neural networks, which is the inherent tendency to learn generalizable hypotheses rather than merely memorizing the training data. It presents evidence that deep networks are "lazy" in the sense that they tend to learn simpler rules before more complex ones. The thesis also proposes that simplicity in deep learning is preconditioned by the implicit priors ingrained in network architectures and training procedures.
Detailed Information
| Author: | ['Phạm Đăng Dũng'] |
|---|---|
| Publication Year: | 2022 |
| Pages: | 78 |
| Language: | English |
| Format: | |
| Price: | FREE |
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