| Unified visual transformer compression S Yu, T Chen, J Shen, H Yuan, J Tan, S Yang, J Liu, Z Wang arXiv preprint arXiv:2203.08243, 2022 | 65 | 2022 |
| Learning a Minimax Optimizer: A Pilot Study J Shen, X Chen, H Heaton, T Chen, J Liu, W Yin, Z Wang International Conference on Learning Representations (ICLR), 2021 | 26 | 2021 |
| UMEC: Unified model and embedding compression for efficient recommendation systems J Shen, S Gui, H Wang, J Tan, Z Wang, J Liu International Conference on Learning Representations (ICLR), 2021 | 18* | 2021 |
| Eliminating the Invariance on the Loss Landscape of Linear Autoencoders R Oftadeh, J Shen, Z Wang, D Shell International Conference on Machine Learning (ICML), 2020 | 10 | 2020 |
| The 2020 low-power computer vision challenge X Hu, MC Chang, Y Chen, R Sridhar, Z Hu, Y Xue, Z Wu, P Pi, J Shen, ... 2021 IEEE 3rd International Conference on Artificial Intelligence Circuits …, 2021 | 7 | 2021 |
| E2vts: energy-efficient video text spotting from unmanned aerial vehicles Z Hu, P Pi, Z Wu, Y Xue, J Shen, J Tan, X Lian, Z Wang, J Liu Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 3 | 2021 |
| An End-to-End Framework for Unified Compression and Learning to Optimize the Minimax Problem J Shen Texas A&M University, 2022 | | 2022 |
| Neural Networks for Principal Component Analysis: A New Loss Function Provably Yields Ordered Exact Eigenvectors R Oftadeh, J Shen, Z Wang, D Shell | | 2019 |
Zhangyang (Atlas) WangUniversity of Texas at Austin & Picsart AI ResearchVerified email at utexas.edu
