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Hessians - A tool for debugging neural network optimization

rohanvarma.me

Optimizing deep neural networks has long followed a general tried-and-true template. Generally, we randomly initialize our weights, which can be thought of as randomly picking a place on the “hill” which is the optimization landscape. There are some tricks we can do to achieve better initialization schemes, such as the He or Xavier initialization.

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