| Triangle Attack: A Query-efficient Decision-based Adversarial Attack X Wang, Z Zhang, K Tong, D Gong, K He, Z Li, W Liu ECCV 2022, 2022 | 43 | 2022 |
| Structure invariant transformation for better adversarial transferability X Wang, Z Zhang, J Zhang ICCV 2023, 2023 | 19 | 2023 |
| Noise Optimization for Artificial Neural Networks L Xiao, Z Zhang, J Jiang, Y Peng CASE 2022, T-ASE 2024, 2021 | 13 | 2021 |
| Video understanding with large language models: A survey Y Tang, J Bi, S Xu, L Song, S Liang, T Wang, D Zhang, J An, J Lin, R Zhu, ... arXiv preprint arXiv:2312.17432, 2023 | 7 | 2023 |
| Diversifying the High-level Features for better Adversarial Transferability Z Wang*, Z Zhang* (equal contribution), S Liang, X Wang BMVC 2023, 2023 | 6 | 2023 |
| One Forward is Enough for Neural Network Training via Likelihood Ratio Method J Jiang*, Z Zhang* (equal contribution), C Xu, Z Yu, Y Peng ICLR 2024, 2024 | 5* | 2024 |
| High-Performance Tensor Learning Primitives Using GPU Tensor Cores XY Liu*, Z Zhang* (equal contribution), Z Wang, H Lu, X Wang, A Walid IEEE Transactions on Computers, 2022 | 4 | 2022 |
| Bag of tricks to boost adversarial transferability Z Zhang, R Zhu, W Yao, X Wang, C Xu Technical report, 2024 | 3 | 2024 |
| How Robust is your Fair Model? Exploring the Robustness of Diverse Fairness Strategies E Small, W Shao, Z Zhang, P Liu, J Chan, K Sokol, F Salim Data Mining and Knowledge Discovery, 2022 | 2 | 2022 |
| A Novel Noise Injection-based Training Scheme for Better Model Robustness Z Zhang, J Jiang, M Chen, Z Wang, Y Peng, Z Yu Technical report, 2022 | 2 | 2022 |
| Random Smooth-based Certified Defense against Text Adversarial Attack Z Zhang, W Yao, S Liang, C Xu EACL 2024, 2024 | 1 | 2024 |
| Forward Learning for Gradient-based Black-box Saliency Map Generation Z Zhang, M Feng, J Jiang, R Zhu, Y Peng, C Xu arXiv preprint arXiv:2403.15603, 2024 | | 2024 |
| Discover and Mitigate Multiple Biased Subgroups in Image Classifiers Z Zhang, M Feng, Z Li, C Xu CVPR 2024, 2024 | | 2024 |
| Approximated Likelihood Ratio: A Forward-Only and Parallel Framework for Boosting Neural Network Training Z Zhang, J Jiang, Z Liu, S Liang, Y Peng, C Xu arXiv preprint arXiv:2403.12320, 2024 | | 2024 |
| Learning to Transform Dynamically for Better Adversarial Transferability Rongyi Zhu*, Zeliang Zhang* (equal contribution, project lead), Susan Liang ... CVPR 2024, 2024 | | 2024 |
| Scalable CP Decomposition for Tensor Learning using GPU Tensor Cores Z Zhang, Z Liu, S Liang, Z Wang, Y Zhu, C Ding, C Xu DAC 2024 WIP, 2023 | | 2023 |
| Classical Simulation of Quantum Circuits: Parallel Environments and Benchmark XY Liu, Z Zhang NeurlPS 2023 Datasets and Benchmarks Track, 2023 | | 2023 |
| DHN: Deep Hamiltonian Network for Variational Reinforcement Learning Z Zhang, Y Wang, Z Liu, XY Liu NeurlPS 2021 QTNML W, 2021 | | 2021 |
| Trillion-Tensor: Trillion-Scale CP Tensor Decomposition Zeliang Zhang, Xiao-Yang Liu, Pan Zhou IJCAI 2020 TNRML W, 2020 | | 2020 |
| Parallel TTr1-Tensor: Randomized Compression-based Scheme for Tensor Train Rank-1 Decomposition Z Zhang, J Zhang, G Lin, Z Yin, K He NeurlPS 2020 QTNML W, 2020 | | 2020 |
Xiaosen WangHuazhong university of Science and TechnologyVerified email at hust.edu.cn
