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Neural models in recent years have been successful in almost every field including extremely complex problem statements. However, these models are huge in size, with millions (and billions) of…
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Scooped by Juliette Decugis |
Scoop.it!
Juliette Decugis's insight:
A comprehensive introduction to knowledge distillation, a new way to compress neural networks. Neural networks fascinate the machine learning community however there is one issue: they require millions to billions of parameters. Imagine if networks could teach each other reduced versions of their information while achieving the same results.
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