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Exploring the Granularity of Sparsity in Convolutional Neural Networks.

H. Mao, S. Han, J. Pool, W. Li, X. Liu, Y. Wang, and W. Dally. CVPR Workshops, page 1927-1934. IEEE Computer Society, (2017)

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Exploring the Granularity of Sparsity in Convolutional Neural Networks.H. Mao, S. Han, J. Pool, W. Li, X. Liu, Y. Wang, and W. Dally. CVPR Workshops, page 1927-1934. IEEE Computer Society, (2017)Exploring the Regularity of Sparse Structure in Convolutional Neural Networks.H. Mao, S. Han, J. Pool, W. Li, X. Liu, Y. Wang, and W. Dally. CoRR, (2017)Lossless compression of variable-precision floating-point buffers on GPUs.J. Pool, A. Lastra, and M. Singh. I3D, page 47-54. ACM, (2012)Learning both Weights and Connections for Efficient Neural Networks.S. Han, J. Pool, J. Tran, and W. Dally. CoRR, (2015)Buddy Compression: Enabling Larger Memory for Deep Learning and HPC Workloads on GPUs.E. Choukse, M. Sullivan, M. O'Connor, M. Erez, J. Pool, D. Nellans, and S. Keckler. CoRR, (2019)Energy-precision tradeoffs in mobile Graphics Processing Units.J. Pool, A. Lastra, and M. Singh. ICCD, page 60-67. IEEE Computer Society, (2008)Structurally Sparsified Backward Propagation for Faster Long Short-Term Memory Training.M. Zhu, J. Clemons, J. Pool, M. Rhu, S. Keckler, and Y. Xie. CoRR, (2018)Precision Selection for Energy-Effi cient Pixel Shaders.J. Pool, A. Lastra, and M. Singh. High Performance Graphics, page 159-168. ACM, (2011)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)Efficient Sparse-Winograd Convolutional Neural Networks.X. Liu, J. Pool, S. Han, and W. Dally. ICLR (Poster), OpenReview.net, (2018)

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Exploring the Granularity of Sparsity in Convolutional Neural Networks.

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Disambiguation of "Pool, Jeff"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Exploring the Granularity of Sparsity in Convolutional Neural Networks.

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Exploring the Granularity of Sparsity in Convolutional Neural Networks.