| Bridging mode connectivity in loss landscapes and adversarial robustness P Zhao, PY Chen, P Das, KN Ramamurthy, X Lin arXiv preprint arXiv:2005.00060, 2020 | 232 | 2020 |
| Structured adversarial attack: Towards general implementation and better interpretability K Xu, S Liu, P Zhao, PY Chen, H Zhang, Q Fan, D Erdogmus, Y Wang, ... arXiv preprint arXiv:1808.01664, 2018 | 189 | 2018 |
| Fault sneaking attack: A stealthy framework for misleading deep neural networks P Zhao, S Wang, C Gongye, Y Wang, Y Fei, X Lin Proceedings of the 56th Annual Design Automation Conference 2019, 1-6, 2019 | 90 | 2019 |
| Defensive dropout for hardening deep neural networks under adversarial attacks S Wang, X Wang, P Zhao, W Wen, D Kaeli, P Chin, X Lin 2018 IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 1-8, 2018 | 90 | 2018 |
| On the design of black-box adversarial examples by leveraging gradient-free optimization and operator splitting method P Zhao, S Liu, PY Chen, N Hoang, K Xu, B Kailkhura, X Lin Proceedings of the IEEE/CVF International Conference on Computer Vision, 121-130, 2019 | 80 | 2019 |
| Robust beamforming design for sum secrecy rate optimization in MU-MISO networks P Zhao, M Zhang, H Yu, H Luo, W Chen IEEE Transactions on Information forensics and Security 10 (9), 1812-1823, 2015 | 70 | 2015 |
| A deep reinforcement learning framework for optimizing fuel economy of hybrid electric vehicles P Zhao, Y Wang, N Chang, Q Zhu, X Lin 2018 23rd Asia and South Pacific design automation conference (ASP-DAC), 196-202, 2018 | 67 | 2018 |
| Advancing model pruning via bi-level optimization Y Zhang, Y Yao, P Ram, P Zhao, T Chen, M Hong, Y Wang, S Liu Advances in Neural Information Processing Systems 35, 18309-18326, 2022 | 66 | 2022 |
| Defending against backdoor attack on deep neural networks K Xu, S Liu, PY Chen, P Zhao, X Lin arXiv preprint arXiv:2002.12162, 2020 | 59 | 2020 |
| 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 |
| Towards query-efficient black-box adversary with zeroth-order natural gradient descent P Zhao, PY Chen, S Wang, X Lin Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 6909-6916, 2020 | 53 | 2020 |
| Interpreting adversarial examples by activation promotion and suppression K Xu, S Liu, G Zhang, M Sun, P Zhao, Q Fan, C Gan, X Lin arXiv preprint arXiv:1904.02057, 2019 | 47 | 2019 |
| Pruning-as-search: Efficient neural architecture search via channel pruning and structural reparameterization Y Li, P Zhao, G Yuan, X Lin, Y Wang, X Chen arXiv preprint arXiv:2206.01198, 2022 | 45 | 2022 |
| An admm-based universal framework for adversarial attacks on deep neural networks P Zhao, S Liu, Y Wang, X Lin Proceedings of the 26th ACM international conference on Multimedia, 1065-1073, 2018 | 40 | 2018 |
| 3D CNN acceleration on FPGA using hardware-aware pruning M Sun, P Zhao, M Gungor, M Pedram, M Leeser, X Lin 2020 57th ACM/IEEE Design Automation Conference (DAC), 1-6, 2020 | 39 | 2020 |
| Towards certificated model robustness against weight perturbations TW Weng, P Zhao, S Liu, PY Chen, X Lin, L Daniel Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 6356-6363, 2020 | 36 | 2020 |
| 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 | 35 | 2021 |
| 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, ... European Conference on Computer Vision, 92-111, 2022 | 31 | 2022 |
| Defending dnn adversarial attacks with pruning and logits augmentation S Wang, X Wang, S Ye, P Zhao, X Lin 2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP …, 2018 | 31 | 2018 |
| Characteristic examples: High-robustness, low-transferability fingerprinting of neural networks S Wang, X Wang, PY Chen, P Zhao, X Lin International Joint Conferences on Artificial Intelligence Organization (IJCAI), 2021 | 25 | 2021 |
Xue LinNortheastern UniversityE-mailová adresa ověřena na: northeastern.edu