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Hands-On One-shot Learning with Python

You're reading from   Hands-On One-shot Learning with Python Learn to implement fast and accurate deep learning models with fewer training samples using PyTorch

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Product type Paperback
Published in Apr 2020
Publisher Packt
ISBN-13 9781838825461
Length 156 pages
Edition 1st Edition
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Authors (2):
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Ankush Garg Ankush Garg
Author Profile Icon Ankush Garg
Ankush Garg
Shruti Jadon Shruti Jadon
Author Profile Icon Shruti Jadon
Shruti Jadon
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Toc

Table of Contents (11) Chapters Close

Memory-augmented neural networks

The goal of MANNs is to excel at one-shot learning tasks. The NMT controller, as we read earlier, uses both content-based addressing and location-based addressing. On the other hand, the MANN controller uses only content-based addressing. There are two reasons for this. One reason is that location-based addressing is not required for one-shot learning tasks. In this task, for a given input, there are only two actions that a controller might need to take and both actions are content dependent and not location dependent. One action is taken when the input is very similar to a previously seen input, in which case we can update the current contents of the memory. The other action is taken when the current input is not similar to previously seen inputs, in which case we don't want to overwrite the recent information; instead, we write to the least...

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