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Deep Compression follows a pipeline procedure involving Pruning, Quantization and Huffman Coding to compress deep neural network models sizes by 35x-40x. We implemented (pseudo) pruning similar to the first stage of the pipeline on LeNet-5 and decreased it's download bandwidth by 65% (after (tensorlfow) quantization & gzip compression).
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Deep Compression follows a pipeline procedure involving Pruning, Quantization and Huffman Coding to compress deep neural network models sizes by 35x-40x. We implemented (pseudo) pruning similar to the first stage of the pipeline on LeNet-5 and decreased it's download bandwidth by 65% (after (tensorlfow) quantization & gzip compression).
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