| Admm-nn: An algorithm-hardware co-design framework of dnns using alternating direction methods of multipliers A Ren, T Zhang, S Ye, J Li, W Xu, X Qian, X Lin, Y Wang Proceedings of the Twenty-Fourth International Conference on Architectural …, 2019 | 198 | 2019 |
| Adam-admm: A unified, systematic framework of structured weight pruning for dnns T Zhang, K Zhang, S Ye, J Li, J Tang, W Wen, X Lin, M Fardad, Y Wang arXiv preprint arXiv:1807.11091 2 (3), 2018 | 76 | 2018 |
| A unified framework of DNN weight pruning and weight clustering/quantization using ADMM S Ye, T Zhang, K Zhang, J Li, J Xie, Y Liang, S Liu, X Lin, Y Wang arXiv preprint arXiv:1811.01907, 2018 | 66 | 2018 |
| Progressive weight pruning of deep neural networks using ADMM S Ye, T Zhang, K Zhang, J Li, K Xu, Y Yang, F Yu, J Tang, M Fardad, S Liu, ... arXiv preprint arXiv:1810.07378, 2018 | 53 | 2018 |
| Sgcn: A graph sparsifier based on graph convolutional networks J Li, T Zhang, H Tian, S Jin, M Fardad, R Zafarani Advances in Knowledge Discovery and Data Mining: 24th Pacific-Asia …, 2020 | 47 | 2020 |
| 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 | 27 | 2018 |
| 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 | 15 | 2019 |
| Graph sparsification with graph convolutional networks J Li, T Zhang, H Tian, S Jin, M Fardad, R Zafarani International Journal of Data Science and Analytics, 1-14, 2022 | 12 | 2022 |
| Linguistic-style-aware neural networks for fake news detection X Zhou, J Li, Q Li, R Zafarani arXiv preprint arXiv:2301.02792, 2023 | 6 | 2023 |
| Adversparse: An adversarial attack framework for deep spatial-temporal graph neural networks J Li, T Zhang, S Jin, M Fardad, R Zafarani ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022 | 5 | 2022 |
| HetGPT: Harnessing the Power of Prompt Tuning in Pre-Trained Heterogeneous Graph Neural Networks Y Ma, N Yan, J Li, M Mortazavi, NV Chawla The ACM Web Conference 2024, 2023 | 4 | 2023 |
| A spectral representation of networks: The path of subgraphs S Jin, H Tian, J Li, R Zafarani Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | 4 | 2022 |
| A Spectral Measure for Network Robustness: Assessment, Design, and Evolution S Jin, R Ma, J Li, S Eftekharnejad, R Zafarani IEEE International Conference on Knowledge Graph (ICKG-2022), 2022 | 1 | 2022 |
| FaceGANs: Stable Generative Adversarial Networks with High-Quality Images J Li, Z Zhan, C Ding, Y Wang | 1 | 2018 |
| Semi-Supervised Graph Ultra-Sparsifier Using Reweighted ℓ1 Optimization J Li, T Zhang, S Jin, R Zafarani ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023 | | 2023 |
Tianyun ZhangCleveland State University在 csuohio.edu 的电子邮件经过验证
