Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding
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Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding
Neural networks are both computationally intensive and memory intensive, making them difficult to deploy on embedded systems with limited hardware resources. To address this limitation, we introduce "deep compression", a three stage pipeline: pruning, trained quantization and Huffman coding, that work together to reduce the storage requirement ...
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