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Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding

, , and . (2015)cite arxiv:1510.00149Comment: Published as a conference paper at ICLR 2016 (oral).

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A Delay Metric for Video Object Detection: What Average Precision Fails to Tell., , and . ICCV, page 573-582. IEEE, (2019)Trained Ternary Quantization., , , and . ICLR (Poster), OpenReview.net, (2017)EIE: Efficient Inference Engine on Compressed Deep Neural Network., , , , , , and . ISCA, page 243-254. IEEE Computer Society, (2016)DSD: Regularizing Deep Neural Networks with Dense-Sparse-Dense Training Flow., , , , , , , , and . CoRR, (2016)Efficient Sparse-Winograd Convolutional Neural Networks., , , and . ICLR (Workshop), OpenReview.net, (2017)Deep Compression: Compressing Deep Neural Network with Pruning, Trained Quantization and Huffman Coding., , and . ICLR, (2016)Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding, , and . (2015)cite arxiv:1510.00149Comment: Published as a conference paper at ICLR 2016 (oral).VILA: On Pre-training for Visual Language Models., , , , , , , , , and . CoRR, (2023)CaTDet: Cascaded Tracked Detector for Efficient Object Detection from Video., , and . CoRR, (2018)Exploring the Regularity of Sparse Structure in Convolutional Neural Networks., , , , , , and . CoRR, (2017)