| 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 | 97 | 2021 |
| Radio frequency fingerprinting on the edge T Jian, Y Gong, Z Zhan, R Shi, N Soltani, Z Wang, J Dy, K Chowdhury, ... IEEE Transactions on Mobile Computing 21 (11), 4078-4093, 2021 | 65 | 2021 |
| Sparcl: Sparse continual learning on the edge Z Zhan, Z Wang, Y Gong, G Yuan, W Niu, T Jian, B Ren, S Ioannidis, ... NeurIPS'22, 2022 | 62* | 2022 |
| 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 | 57 | 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 | 34 | 2021 |
| A privacy-preserving-oriented dnn pruning and mobile acceleration framework Y Gong, Z Zhan, Z Li, W Niu, X Ma, W Wang, B Ren, C Ding, X Lin, X Xu, ... Proceedings of the 2020 on Great Lakes Symposium on VLSI, 119-124, 2020 | 30 | 2020 |
| Compiler-Aware Neural Architecture Search for On-Mobile Real-time Super-Resolution Y Wu, Y Gong, P Zhao, Y Li, Z Zhan, W Niu, H Tang, M Qin, B Ren, ... ECCV'22, 2022 | 29 | 2022 |
| A unified dnn weight pruning framework using reweighted optimization methods T Zhang, X Ma, Z Zhan, S Zhou, C Ding, M Fardad, Y Wang 2021 58th ACM/IEEE Design Automation Conference (DAC), 493-498, 2021 | 29 | 2021 |
| SS-Auto: A single-shot, automatic structured weight pruning framework of DNNs with ultra-high efficiency Z Li, Y Gong, X Ma, S Liu, M Sun, Z Zhan, Z Kong, G Yuan, Y Wang arXiv preprint arXiv:2001.08839, 2020 | 21 | 2020 |
| Universal approximation property and equivalence of stochastic computing-based neural networks and binary neural networks Y Wang, Z Zhan, L Zhao, J Tang, S Wang, J Li, B Yuan, W Wen, X Lin Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 5369-5376, 2019 | 16 | 2019 |
| Blk-rew: A unified block-based dnn pruning framework using reweighted regularization method X Ma, Z Li, Y Gong, T Zhang, W Niu, Z Zhan, P Zhao, J Tang, X Lin, B Ren, ... arXiv preprint arXiv:2001.08357, 2020 | 15 | 2020 |
| Towards real-time DNN inference on mobile platforms with model pruning and compiler optimization W Niu, P Zhao, Z Zhan, X Lin, Y Wang, B Ren Proceedings of the Twenty-Ninth International Joint Conference on Artificial …, 2020 | 12 | 2020 |
| DualHSIC: HSIC-Bottleneck and Alignment for Continual Learning Z Zhan, Z Wang, Y Gong, Y Shao, S Ioannidis, Y Wang, J Dy ICML'23, 2023 | 11 | 2023 |
| Chic experience-driven scheduling in machine learning clusters Y Gong, B Li, B Liang, Z Zhan Proceedings of the International Symposium on Quality of Service, 1-10, 2019 | 11 | 2019 |
| Diffclass: Diffusion-based class incremental learning Z Meng, J Zhang, C Yang, Z Zhan, P Zhao, Y Wang European Conference on Computer Vision, 142-159, 2024 | 10 | 2024 |
| Blcr: Towards real-time dnn execution with block-based reweighted pruning X Ma, G Yuan, Z Li, Y Gong, T Zhang, W Niu, Z Zhan, P Zhao, N Liu, ... 2022 23rd International Symposium on Quality Electronic Design (ISQED), 1-8, 2022 | 10 | 2022 |
| Automatic Mapping of the Best-Suited DNN Pruning Schemes for Real-Time Mobile Acceleration Y Gong, G Yuan, Z Zhan, W Niu, Z Li, P Zhao, Y Cai, S Liu, B Ren, X Lin, ... ACM Transactions on Design Automation of Electronic Systems (TODAES) 27 (5), 2021 | 10 | 2021 |
| All-in-One: A Highly Representative DNN Pruning Framework for Edge Devices with Dynamic Power Management Y Gong*, Z Zhan*, P Zhao, Y Wu, C Wu, C Ding, W Jiang, M Qin, Y Wang 2022 IEEE/ACM International Conference On Computer Aided Design (ICCAD), 1-8, 2022 | 9 | 2022 |
| A unified dnn weight compression framework using reweighted optimization methods T Zhang, X Ma, Z Zhan, S Zhou, M Qin, F Sun, YK Chen, C Ding, ... arXiv preprint arXiv:2004.05531, 2020 | 7 | 2020 |
| Exploring token pruning in vision state space models Z Zhan, Z Kong, Y Gong, Y Wu, Z Meng, H Zheng, X Shen, S Ioannidis, ... arXiv preprint arXiv:2409.18962, 2024 | 5 | 2024 |
Yanzhi WangNortheastern UniversityDirección de correo verificada de northeastern.edu
