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I. Hubara, Courbariaux, M. , Soudry, D. , El-Yaniv, R. , and Bengio, Y. , Binarized neural networks, Advances in neural information processing systems. pp. 4107–4115, 2016.
M. Courbariaux, Hubara, I. , Soudry, D. , El-Yaniv, R. , and Bengio, Y. , Binarized neural networks: Training deep neural networks with weights and activations constrained to+ 1 or-1, arXiv preprint arXiv:1602.02830, 2016.
M. Kim and Smaragdis, P. , Bitwise neural networks, arXiv preprint arXiv:1601.06071, 2016.
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Y. Shen, Zhu, G. , Li, J. , and Zhu, Z. , Compressed Sensing Image Reconstruction Algorithm by Dictionary Learning, Proceedings of International Conference on Internet Multimedia Computing and Service. ACM, p. 193, 2014.
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Y. Chen, Luo, T. , Liu, S. , Zhang, S. , He, L. , Wang, J. , Li, L. , Chen, T. , Xu, Z. , Sun, N. , and , , Dadiannao: A machine-learning supercomputer, Proceedings of the 47th Annual IEEE/ACM International Symposium on Microarchitecture. IEEE Computer Society, pp. 609–622, 2014.
Z. Yu, Trindade, B. Machado, Green, M. , Zhang, Z. , Sneha, P. , Bank-Tavakoli, E. , Pawlowicz, C. , and Ren, F. , A Data-Driven Approach for Automated Integrated Circuit Segmentation of Scan Electron Microscopy Images, The 29th IEEE International Conference on Image Processing (ICIP). Bordeaux, France, 2022. (1.03 MB)
J. Schmidhuber, Deep learning in neural networks: An overview, Neural networks, vol. 61, pp. 85–117, 2015.
T. Chen, Du, Z. , Sun, N. , Wang, J. , Wu, C. , Chen, Y. , and Temam, O. , Diannao: A small-footprint high-throughput accelerator for ubiquitous machine-learning, ACM Sigplan Notices, vol. 49. ACM, pp. 269–284, 2014.
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T. S. Czajkowski, Aydonat, U. , Denisenko, D. , Freeman, J. , Kinsner, M. , Neto, D. , Wong, J. , Yiannacouras, P. , and Singh, D. P. , From OpenCL to high-performance hardware on FPGAs, Field Programmable Logic and Applications (FPL), 2012 22nd International Conference on. IEEE, pp. 531–534, 2012.
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C. Szegedy, Liu, W. , Jia, Y. , Sermanet, P. , Reed, S. , Anguelov, D. , Erhan, D. , Vanhoucke, V. , and Rabinovich, A. , Going deeper with convolutions, Proceedings of the IEEE conference on computer vision and pattern recognition. pp. 1–9, 2015.
C. Szegedy, Liu, W. , Jia, Y. , Sermanet, P. , Reed, S. , Anguelov, D. , Erhan, D. , Vanhoucke, V. , and Rabinovich, A. , Going deeper with convolutions, Proceedings of the IEEE conference on computer vision and pattern recognition. pp. 1–9, 2015.
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A. Krizhevsky, Sutskever, I. , and Hinton, G. E. , Imagenet classification with deep convolutional neural networks, Advances in neural information processing systems. pp. 1097–1105, 2012.
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K. Xu, Qin, M. , Sun, F. , Wang, Y. , Chen, Y. - K. , and Ren, F. , Learning in the Frequency Domain, IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). Seattle, WA, pp. 1740-1749, 2020. (4.98 MB)
J. Martin Duarte-Carvajalino and Sapiro, G. , Learning to sense sparse signals: Simultaneous sensing matrix and sparsifying dictionary optimization, IEEE Transactions on Image Processing, vol. 18, pp. 1395–1408, 2009.
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W. Xu, Huang, M. - C. , Liu, J. J. , Ren, F. , Shen, X. , Liu, X. , and Sarrafzadeh, M. , mCOPD: Mobile Phone Based Lung Function Diagnosis and Exercise System for COPD, Proceedings of the 6th International Conference on Pervasive Technologies Related to Assistive Environments (PETRA). ACM, 2013. (646.4 KB)
W. Xu, Huang, M. - C. , Liu, J. J. , Ren, F. , Shen, X. , Liu, X. , and Sarrafzadeh, M. , mCOPD: Mobile Phone Based Lung Function Diagnosis and Exercise System for COPD, Proceedings of the 6th International Conference on Pervasive Technologies Related to Assistive Environments (PETRA). ACM, 2013. (646.4 KB)
X. Zhou, Peng, Y. , Long, C. , Ren, F. , and Shi, C. , MoNet3D: Towards Accurate Monocular 3D Object Localization in Real Time, The Thirty-seventh International Conference on Machine Learning. Virtual Event, 2020. (9.74 MB)
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C. Hegde, Sankaranarayanan, A. C. , Yin, W. , and Baraniuk, R. G. , NuMax: A convex approach for learning near-isometric linear embeddings, IEEE Transactions on Signal Processing, vol. 63, pp. 6109–6121, 2015.
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C. Zhang, Li, P. , Sun, G. , Guan, Y. , Xiao, B. , and Cong, J. , Optimizing fpga-based accelerator design for deep convolutional neural networks, Proceedings of the 2015 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays. ACM, pp. 161–170, 2015.
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M. Zinkevich, Weimer, M. , Li, L. , and Smola, A. J. , Parallelized stochastic gradient descent, Advances in neural information processing systems. pp. 2595–2603, 2010.