| UNDERSTANDING STRAIGHT-THROUGH ESTIMATOR IN TRAINING ACTIVATION QUANTIZED NEURAL NETS P Yin, J Lyu, S Zhang, S Osher, Y Qi, J Xin Seventh International Conference on Learning Representations (ICLR), 2019 | 179 | 2019 |
| Minimization of Transformed L_1 Penalty: Theory, Difference of Convex Function Algorithm, and Robust Application in Compressed Sensing S Zhang, J Xin Mathematical Programming 169 (1), 307 - 336, 2018 | 97 | 2018 |
| Binaryrelax: A relaxation approach for training deep neural networks with quantized weights P Yin, S Zhang, J Lyu, S Osher, Y Qi, J Xin SIAM Journal on Imaging Sciences, 2018 | 77 | 2018 |
| Blended coarse gradient descent for full quantization of deep neural networks P Yin, S Zhang, J Lyu, S Osher, Y Qi, J Xin Research in the Mathematical Sciences, 2018 | 64 | 2018 |
| Minimization of transformed penalty: Closed form representation and iterative thresholding algorithms S Zhang, J Xin Communications in Mathematical Sciences 15 (2), 511 – 537, 2017 | 55 | 2017 |
| Quantization and Training of Low Bit-Width Convolutional Neural Networks for Object Detection P Yin, S Zhang, Y Qi, J Xin Journal of Computational Mathematics 37 (3), 349 - 360, 2018 | 54* | 2018 |
| TRP: Trained Rank Pruning for Efficient Deep Neural Networks Y Xu, Y Li, S Zhang, W Wen, B Wang, Y Qi, Y Chen, W Lin, H Xiong International Joint Conference on Artificial Intelligence (IJCAI) 2020, 2020 | 42 | 2020 |
| Trained Rank Pruning for Efficient Deep Neural Networks Y Xu, Y Li, S Zhang, W Wen, B Wang, Y Qi, Y Chen, W Lin, H Xiong The NeurIPS 2019 Workshop on Energy Efficient Machine Learning and Cognitive …, 2018 | 32 | 2018 |
| Transformed Schatten-1 iterative thresholding algorithms for low rank matrix completion S Zhang, P Yin, J Xin Communications in Mathematical Sciences 15 (3), 839 – 862, 2017 | 26* | 2017 |
| Autoshufflenet: Learning permutation matrices via an exact lipschitz continuous penalty in deep convolutional neural networks J Lyu, S Zhang, Y Qi, J Xin Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020 | 21 | 2020 |
| Channel Pruning for Deep Neural Networks via a Relaxed Groupwise Splitting Method B Yang, J Xin, J Lyu, S Zhang, Y Qi International Conference on Artificial Intelligence for Industries (AI4I), 2019 | 12 | 2019 |
| Structured sparsity of convolutional neural networks via nonconvex sparse group regularization K Bui, F Park, S Zhang, Y Qi, J Xin Frontiers in applied mathematics and statistics 6, 529564, 2021 | 9 | 2021 |
| DAC: Data-free Automatic Acceleration of Convolutional Networks X Li, S Zhang, B Jiang, Y Qi, MC Chuah, N Bi Winter Conference on Applications of Computer Vision (WACV), 2019 | 7 | 2019 |
| DNQ: Dynamic Network Quantization Y Xu, S Zhang, Y Qi, J Guo, W Lin, H Xiong 2019 Data Compression Conference (DCC), 610-610, 2019 | 6 | 2019 |
| Nonconvex regularization for network slimming: compressing cnns even more K Bui, F Park, S Zhang, Y Qi, J Xin Advances in Visual Computing: 15th International Symposium, ISVC 2020, San …, 2020 | 5 | 2020 |
| Improving network slimming with nonconvex regularization K Bui, F Park, S Zhang, Y Qi, J Xin IEEE Access 9, 115292-115314, 2021 | 4 | 2021 |
| Weakly-supervised degree of eye-closeness estimation E Mequanint, S Zhang, B Forutanpour, Y Qi, N Bi Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 4 | 2019 |
| Tiny-Hourglassnet: An efficient design for 3D human pose estimation B Shi, Y Xu, W Dai, B Wang, S Zhang, C Li, J Zou, H Xiong 2020 IEEE International Conference on Image Processing (ICIP), 1491-1495, 2020 | 2 | 2020 |
| Regularized Structured Sparsity Convolutional Neural Networks K Bui, F Park, S Zhang, Y Qi, J Xin arXiv preprint arXiv:1912.07868, 2019 | 2 | 2019 |
| An optimal-order error estimate for the mass-conservative characteristic finite element scheme H Wang, H Rui, S Zhang Applied Mathematics and Computation 218 (20), 10271-10278, 2012 | 2 | 2012 |
Jack XinChancellor's Professor of Mathematics, UC IrvineVerified email at uci.edu
