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Neural Networks Minimization Using Input Importance

What is it about?

Proposing a new methodology to prune the neural network based on input performance. The approach utilizes the nature of the input data and its importance, the more is the importance of the input data, the more likely is to keep its input link to hidden layer, and the lower is the importance of the input data, the less likely is to keep its input link to hidden layer.

Why is it important?

neural networks nowadays are used commonly in machine learning. Due to complexity of neural networks, the learning process takes a lot of time, one way to expedite the learning process is to minimize the size of the neural network. This process is done by what so called pruning.

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Nabil Hewahi
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