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ESE: Efficient Speech Recognition Engine with Sparse LSTM on FPGA.

S. Han, J. Kang, H. Mao, Y. Hu, X. Li, Y. Li, D. Xie, H. Luo, S. Yao, Y. Wang, H. Yang, and W. Dally. FPGA, page 75-84. ACM, (2017)

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EIE: Efficient Inference Engine on Compressed Deep Neural Network.S. Han, X. Liu, H. Mao, J. Pu, A. Pedram, M. Horowitz, and W. Dally. ISCA, page 243-254. IEEE Computer Society, (2016)Trained Ternary Quantization.C. Zhu, S. Han, H. Mao, and W. Dally. ICLR (Poster), OpenReview.net, (2017)Towards Real-Time Object Detection on Embedded Systems.H. Mao, S. Yao, T. Tang, B. Li, J. Yao, and Y. Wang. IEEE Trans. Emerging Topics Comput., 6 (3): 417-431 (2018)Deep Compression: Compressing Deep Neural Network with Pruning, Trained Quantization and Huffman Coding.S. Han, H. Mao, and W. Dally. ICLR, (2016)Efficient Sparse-Winograd Convolutional Neural Networks.X. Liu, S. Han, H. Mao, and W. Dally. ICLR (Workshop), OpenReview.net, (2017)DSD: Regularizing Deep Neural Networks with Dense-Sparse-Dense Training Flow.S. Han, J. Pool, S. Narang, H. Mao, S. Tang, E. Elsen, B. Catanzaro, J. Tran, and W. Dally. CoRR, (2016)Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training.Y. Lin, S. Han, H. Mao, Y. Wang, and B. Dally. ICLR (Poster), OpenReview.net, (2018)DSD: Dense-Sparse-Dense Training for Deep Neural Networks.S. Han, J. Pool, S. Narang, H. Mao, E. Gong, S. Tang, E. Elsen, P. Vajda, M. Paluri, J. Tran and 2 other author(s). ICLR (Poster), OpenReview.net, (2017)Rebooting Computing and Low-Power Image Recognition Challenge.Y. Lu, A. Kadin, A. Berg, T. Conte, E. DeBenedictis, R. Garg, G. Gingade, B. Hoang, Y. Huang, B. Li and 10 other author(s). ICCAD, page 927-932. IEEE, (2015)A Delay Metric for Video Object Detection: What Average Precision Fails to Tell.H. Mao, X. Yang, and W. Dally. CoRR, (2019)

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ESE: Efficient Speech Recognition Engine with Sparse LSTM on FPGA.

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copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML ESE: Efficient Speech Recognition Engine with Sparse LSTM on FPGA.

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ESE: Efficient Speech Recognition Engine with Sparse LSTM on FPGA.