Exploring the regularity of sparse structure in convolutional neural networks H Mao, S Han, J Pool, W Li, X Liu, Y Wang, WJ Dally arXiv preprint arXiv:1705.08922, 2017 | 348* | 2017 |
Dsa: More efficient budgeted pruning via differentiable sparsity allocation X Ning, T Zhao, W Li, P Lei, Y Wang, H Yang European Conference on Computer Vision, 592-607, 2020 | 42 | 2020 |
Hu-fu: Hardware and software collaborative attack framework against neural networks W Li, J Yu, X Ning, P Wang, Q Wei, Y Wang, H Yang 2018 IEEE Computer Society Annual Symposium on VLSI (ISVLSI), 482-487, 2018 | 40 | 2018 |
Neural network accelerator comparison K Guo, W Li, K Zhong, Z Zhu, S Zeng, S Han, Y Xie, P Debacker, ... NICS Lab of Tsinghua University. http://nicsefc. ee. tsinghua. edu. cn …, 2020 | 19 | 2020 |
Adversarial vision challenge W Brendel, J Rauber, A Kurakin, N Papernot, B Veliqi, SP Mohanty, ... The NeurIPS'18 Competition, 129-153, 2020 | 17 | 2020 |
FTT-NAS: Discovering fault-tolerant neural architecture W Li, X Ning, G Ge, X Chen, Y Wang, H Yang 2020 25th Asia and South Pacific Design Automation Conference (ASP-DAC), 211-216, 2020 | 15 | 2020 |
Compressed cnn training with fpga-based accelerator K Guo, S Liang, J Yu, X Ning, W Li, Y Wang, H Yang Proceedings of the 2019 ACM/SIGDA International Symposium on Field …, 2019 | 13 | 2019 |
Evaluating efficient performance estimators of neural architectures X Ning, C Tang, W Li, Z Zhou, S Liang, H Yang, Y Wang Advances in Neural Information Processing Systems 34, 12265-12277, 2021 | 11* | 2021 |
Physical adversarial attack on vehicle detector in the carla simulator T Wu, X Ning, W Li, R Huang, H Yang, Y Wang arXiv preprint arXiv:2007.16118, 2020 | 11 | 2020 |
Soft error mitigation for deep convolution neural network on FPGA accelerators W Li, G Ge, K Guo, X Chen, Q Wei, Z Gao, Y Wang, H Yang 2020 2nd IEEE International Conference on Artificial Intelligence Circuits …, 2020 | 7 | 2020 |
Learning student networks in the wild H Chen, T Guo, C Xu, W Li, C Xu, C Xu, Y Wang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 6 | 2021 |
FTT-NAS: Discovering fault-tolerant convolutional neural architecture X Ning, G Ge, W Li, Z Zhu, Y Zheng, X Chen, Z Gao, Y Wang, H Yang ACM Transactions on Design Automation of Electronic Systems (TODAES) 26 (6 …, 2021 | 5 | 2021 |
Multi-shot NAS for discovering adversarially robust convolutional neural architectures at targeted capacities X Ning, J Zhao, W Li, T Zhao, H Yang, Y Wang arXiv preprint arXiv:2012.11835, 2020 | 5* | 2020 |
Brain-inspired multilayer perceptron with spiking neurons W Li, H Chen, J Guo, Z Zhang, Y Wang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 3 | 2022 |
Winograd Algorithm for AdderNet W Li, H Chen, M Huang, X Chen, C Xu, Y Wang International Conference on Machine Learning, 6307-6315, 2021 | 3 | 2021 |
Reliable classification with ensemble convolutional neural networks Z Gao, H Zhang, X Wei, T Yan, K Guo, W Li, Y Wang, P Reviriego 2020 IEEE International Symposium on Defect and Fault Tolerance in VLSI and …, 2020 | 3 | 2020 |
Reliability evaluation of pruned neural networks against errors on parameters Z Gao, X Wei, H Zhang, W Li, G Ge, Y Wang, P Reviriego 2020 IEEE International Symposium on Defect and Fault Tolerance in VLSI and …, 2020 | 3 | 2020 |
aw_nas: A modularized and extensible nas framework X Ning, C Tang, W Li, S Yang, T Zhao, N Zhang, T Lu, S Liang, H Yang, ... arXiv preprint arXiv:2012.10388, 2020 | 2 | 2020 |
Searching for Energy-Efficient Hybrid Adder-Convolution Neural Networks W Li, X Chen, J Bai, X Ning, Y Wang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | | 2022 |