Towards robust neural networks via random self-ensemble X Liu, M Cheng, H Zhang, CJ Hsieh Proceedings of the european conference on computer vision (ECCV), 369-385, 2018 | 532 | 2018 |
Query-efficient hard-label black-box attack: An optimization-based approach M Cheng, T Le, PY Chen, J Yi, H Zhang, CJ Hsieh arXiv preprint arXiv:1807.04457, 2018 | 489 | 2018 |
Sign-opt: A query-efficient hard-label adversarial attack M Cheng, S Singh, P Chen, PY Chen, S Liu, CJ Hsieh arXiv preprint arXiv:1909.10773, 2019 | 293 | 2019 |
Seq2sick: Evaluating the robustness of sequence-to-sequence models with adversarial examples M Cheng, J Yi, PY Chen, H Zhang, CJ Hsieh Proceedings of the AAAI conference on artificial intelligence 34 (04), 3601-3608, 2020 | 273 | 2020 |
Rethinking architecture selection in differentiable NAS R Wang, M Cheng, X Chen, X Tang, CJ Hsieh arXiv preprint arXiv:2108.04392, 2021 | 209 | 2021 |
Drnas: Dirichlet neural architecture search X Chen, R Wang, M Cheng, X Tang, CJ Hsieh arXiv preprint arXiv:2006.10355, 2020 | 147 | 2020 |
Cat: Customized adversarial training for improved robustness M Cheng, Q Lei, PY Chen, I Dhillon, CJ Hsieh arXiv preprint arXiv:2002.06789, 2020 | 126 | 2020 |
On the robustness of self-attentive models YL Hsieh, M Cheng, DC Juan, W Wei, WL Hsu, CJ Hsieh Proceedings of the 57th Annual Meeting of the Association for Computational …, 2019 | 119 | 2019 |
Attack graph convolutional networks by adding fake nodes X Wang, M Cheng, J Eaton, CJ Hsieh, F Wu arXiv preprint arXiv:1810.10751, 2018 | 99 | 2018 |
Feddm: Iterative distribution matching for communication-efficient federated learning Y Xiong, R Wang, M Cheng, F Yu, CJ Hsieh Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 97 | 2023 |
A review of adversarial attack and defense for classification methods Y Li, M Cheng, CJ Hsieh, TCM Lee The American Statistician 76 (4), 329-345, 2022 | 87 | 2022 |
Fake node attacks on graph convolutional networks X Wang, M Cheng, J Eaton, CJ Hsieh, SF Wu Journal of Computational and Cognitive Engineering 1 (4), 165-173, 2022 | 73 | 2022 |
Evaluating and enhancing the robustness of dialogue systems: A case study on a negotiation agent M Cheng, W Wei, CJ Hsieh Proceedings of the 2019 Conference of the North American Chapter of the …, 2019 | 49 | 2019 |
Evaluating and enhancing the robustness of neural network-based dependency parsing models with adversarial examples X Zheng, J Zeng, Y Zhou, CJ Hsieh, M Cheng, XJ Huang Proceedings of the 58th Annual Meeting of the Association for Computational …, 2020 | 42 | 2020 |
Boosting accuracy and robustness of student models via adaptive adversarial distillation B Huang, M Chen, Y Wang, J Lu, M Cheng, W Wang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 31 | 2023 |
Learning from group comparisons: exploiting higher order interactions Y Li, M Cheng, K Fujii, F Hsieh, CJ Hsieh Advances in Neural Information Processing Systems 31, 2018 | 26 | 2018 |
Random sharpness-aware minimization Y Liu, S Mai, M Cheng, X Chen, CJ Hsieh, Y You Advances in Neural Information Processing Systems 35, 24543-24556, 2022 | 25 | 2022 |
Stochastic zeroth-order optimization via variance reduction method L Liu, M Cheng, CJ Hsieh, D Tao arXiv preprint arXiv:1805.11811, 2018 | 25 | 2018 |
Revisiting personalized federated learning: Robustness against backdoor attacks Z Qin, L Yao, D Chen, Y Li, B Ding, M Cheng Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | 22 | 2023 |
Drattack: Prompt decomposition and reconstruction makes powerful llm jailbreakers X Li, R Wang, M Cheng, T Zhou, CJ Hsieh arXiv preprint arXiv:2402.16914, 2024 | 20 | 2024 |