| CirCNN: accelerating and compressing deep neural networks using block-circulant weight matrices C Ding, S Liao, Y Wang, Z Li, N Liu, Y Zhuo, C Wang, X Qian, Y Bai, ... Proceedings of the 50th Annual IEEE/ACM International Symposium on …, 2017 | 298 | 2017 |
| Efficientformer: Vision transformers at mobilenet speed Y Li, G Yuan, Y Wen, J Hu, G Evangelidis, S Tulyakov, Y Wang, J Ren Advances in Neural Information Processing Systems 35, 12934-12949, 2022 | 113 | 2022 |
| Yolobile: Real-time object detection on mobile devices via compression-compilation co-design Y Cai, H Li, G Yuan, W Niu, Y Li, X Tang, B Ren, Y Wang Proceedings of the AAAI conference on artificial intelligence 35 (2), 955-963, 2021 | 88 | 2021 |
| Spvit: Enabling faster vision transformers via latency-aware soft token pruning Z Kong, P Dong, X Ma, X Meng, W Niu, M Sun, X Shen, G Yuan, B Ren, ... European Conference on Computer Vision, 620-640, 2022 | 75* | 2022 |
| Non-structured DNN weight pruning—Is it beneficial in any platform? X Ma, S Lin, S Ye, Z He, L Zhang, G Yuan, SH Tan, Z Li, D Fan, X Qian, ... IEEE transactions on neural networks and learning systems 33 (9), 4930-4944, 2021 | 72 | 2021 |
| An ultra-efficient memristor-based DNN framework with structured weight pruning and quantization using ADMM G Yuan, X Ma, C Ding, S Lin, T Zhang, ZS Jalali, Y Zhao, L Jiang, ... 2019 IEEE/ACM International Symposium on Low Power Electronics and Design …, 2019 | 54 | 2019 |
| Tiny but accurate: A pruned, quantized and optimized memristor crossbar framework for ultra efficient dnn implementation X Ma, G Yuan, S Lin, C Ding, F Yu, T Liu, W Wen, X Chen, Y Wang 2020 25th Asia and South Pacific design automation conference (ASP-DAC), 301-306, 2020 | 52 | 2020 |
| Sanity checks for lottery tickets: Does your winning ticket really win the jackpot? X Ma, G Yuan, X Shen, T Chen, X Chen, X Chen, N Liu, M Qin, S Liu, ... Advances in Neural Information Processing Systems 34, 12749-12760, 2021 | 47 | 2021 |
| FORMS: Fine-grained polarized ReRAM-based in-situ computation for mixed-signal DNN accelerator G Yuan, P Behnam, Z Li, A Shafiee, S Lin, X Ma, H Liu, X Qian, ... 2021 ACM/IEEE 48th Annual International Symposium on Computer Architecture …, 2021 | 46 | 2021 |
| Teachers do more than teach: Compressing image-to-image models Q Jin, J Ren, OJ Woodford, J Wang, G Yuan, Y Wang, S Tulyakov Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 46 | 2021 |
| Towards ultra-high performance and energy efficiency of deep learning systems: an algorithm-hardware co-optimization framework Y Wang, C Ding, Z Li, G Yuan, S Liao, X Ma, B Yuan, X Qian, J Tang, ... Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 43 | 2018 |
| Resnet can be pruned 60×: Introducing network purification and unused path removal (p-rm) after weight pruning X Ma, G Yuan, S Lin, Z Li, H Sun, Y Wang 2019 IEEE/ACM International Symposium on Nanoscale Architectures (NANOARCH), 1-2, 2019 | 35 | 2019 |
| Zhenglun Kong, Ning Liu, Yifan Gong, Zheng Zhan, Chaoyang He, Qing Jin, et al. Mest: Accurate and fast memory-economic sparse training framework on the edge G Yuan, X Ma, W Niu, Z Li Advances in Neural Information Processing Systems 34 (20838-20850), 2, 2021 | 29 | 2021 |
| Achieving on-mobile real-time super-resolution with neural architecture and pruning search Z Zhan, Y Gong, P Zhao, G Yuan, W Niu, Y Wu, T Zhang, M Jayaweera, ... Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 28 | 2021 |
| Mest: Accurate and fast memory-economic sparse training framework on the edge G Yuan, X Ma, W Niu, Z Li, Z Kong, N Liu, Y Gong, Z Zhan, C He, Q Jin, ... Advances in Neural Information Processing Systems 34, 20838-20850, 2021 | 27 | 2021 |
| Improving DNN fault tolerance using weight pruning and differential crossbar mapping for ReRAM-based edge AI G Yuan, Z Liao, X Ma, Y Cai, Z Kong, X Shen, J Fu, Z Li, C Zhang, H Peng, ... 2021 22nd International Symposium on Quality Electronic Design (ISQED), 135-141, 2021 | 26 | 2021 |
| Structured weight matrices-based hardware accelerators in deep neural networks: Fpgas and asics C Ding, A Ren, G Yuan, X Ma, J Li, N Liu, B Yuan, Y Wang Proceedings of the 2018 on Great Lakes Symposium on VLSI, 353-358, 2018 | 26 | 2018 |
| Lottery Ticket Preserves Weight Correlation: Is It Desirable or Not? N Liu, G Yuan, Z Che, X Shen, X Ma, Q Jin, J Ren, J Tang, S Liu, Y Wang International Conference on Machine Learning, 7011-7020, 2021 | 25 | 2021 |
| Npas: A compiler-aware framework of unified network pruning and architecture search for beyond real-time mobile acceleration Z Li, G Yuan, W Niu, P Zhao, Y Li, Y Cai, X Shen, Z Zhan, Z Kong, Q Jin, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 25 | 2021 |
| An area and energy efficient design of domain-wall memory-based deep convolutional neural networks using stochastic computing X Ma, Y Zhang, G Yuan, A Ren, Z Li, J Han, J Hu, Y Wang 2018 19th International Symposium on Quality Electronic Design (ISQED), 314-321, 2018 | 22 | 2018 |
Yanzhi WangNortheastern UniversityVerified email at northeastern.edu
