Enhancing the Regularization Effect of Weight Pruning in Artificial Neural Networks

4 May 2018Brian BartoldsonAdrian BarbuGordon Erlebacher

Artificial neural networks (ANNs) may not be worth their computational/memory costs when used in mobile phones or embedded devices. Parameter-pruning algorithms combat these costs, with some algorithms capable of removing over 90% of an ANN's weights without harming the ANN's performance... (read more)

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