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About Deep Learning Algorithms Report PDF
This document summarizes deep learning algorithms called sparse autoencoders. It discusses how sparse autoencoders can be used to automatically learn features from unlabeled data. Sparse autoencoders add a sparsity penalty term to the cost function to encourage most hidden units to be inactive for any given input. This leads to a sparse distributed representation that can produce features that are competitive or superior to hand-engineered features. The document provides examples of using sparse autoencoders to learn features from images by encoding pixel grids and reconstructing similar outputs.
Detailed Information
| Author: | ['rohillaanshul12'] |
|---|---|
| Publication Year: | 2014 |
| Pages: | 11 |
| Language: | English |
| Format: | |
| Price: | FREE |
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