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About Why Does Unsupervised Deep Learning Work? - A Perspective From Group Theory
1) The document discusses how group theory can provide insights into why unsupervised deep learning works. 2) It establishes a connection between the interplay of orbits and stabilizers in group actions, and the principle of pretraining layers in deep neural networks one layer at a time. 3) Pretraining can be viewed as searching for features with minimal orbits, which intuitively correspond to simpler features that deep learning networks tend to learn first in each layer.
Detailed Information
| Author: | ['Michael Chiu'] |
|---|---|
| Publication Year: | 2017 |
| Pages: | 14 |
| Language: | English |
| Format: | |
| Price: | FREE |
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