| Zoo: Zeroth order optimization based black-box attacks to deep neural networks without training substitute models PY Chen*, H Zhang*, Y Sharma, J Yi, CJ Hsieh (*Equal Contribution) Proceedings of the 10th ACM workshop on artificial …, 2017 | 1077 | 2017 |
| Can decentralized algorithms outperform centralized algorithms? a case study for decentralized parallel stochastic gradient descent X Lian, C Zhang, H Zhang, CJ Hsieh, W Zhang, J Liu Advances in Neural Information Processing Systems (NIPS) (oral presentation …, 2017 | 603 | 2017 |
| Towards fast computation of certified robustness for relu networks L Weng*, H Zhang*, H Chen, Z Song, CJ Hsieh, L Daniel, D Boning, ... (*Equal Contribution) International Conference on Machine Learning, 5276-5285, 2018 | 475 | 2018 |
| Ead: elastic-net attacks to deep neural networks via adversarial examples PY Chen, Y Sharma, H Zhang, J Yi, CJ Hsieh Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 454 | 2018 |
| Efficient neural network robustness certification with general activation functions H Zhang*, TW Weng*, PY Chen, CJ Hsieh, L Daniel (*Equal Contribution) Advances in Neural Information Processing Systems …, 2018 | 371 | 2018 |
| 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 | 302 | 2018 |
| Evaluating the robustness of neural networks: An extreme value theory approach TW Weng*, H Zhang*, PY Chen, J Yi, D Su, Y Gao, CJ Hsieh, L Daniel (*Equal Contribution) arXiv preprint arXiv:1801.10578, 2018 | 279 | 2018 |
| Is Robustness the Cost of Accuracy?--A Comprehensive Study on the Robustness of 18 Deep Image Classification Models D Su*, H Zhang*, H Chen, J Yi, PY Chen, Y Gao (*Equal Contribution) Proceedings of the European Conference on Computer …, 2018 | 273 | 2018 |
| Provably robust deep learning via adversarially trained smoothed classifiers H Salman, J Li, I Razenshteyn, P Zhang, H Zhang, S Bubeck, G Yang Advances in Neural Information Processing Systems (NeurIPS) (spotlight …, 2019 | 265 | 2019 |
| Spectral and spatial 2D fragmentation-aware routing and spectrum assignment algorithms in elastic optical networks Y Yin, H Zhang, M Zhang, M Xia, Z Zhu, S Dahlfort, SJB Yoo Journal of Optical Communications and Networking 5 (10), A100-A106, 2013 | 253 | 2013 |
| Query-efficient hard-label black-box attack: An optimization-based approach M Cheng, T Le, PY Chen, J Yi, H Zhang, CJ Hsieh International Conference on Learning Representations (ICLR) 2019, 2018 | 237 | 2018 |
| Autozoom: Autoencoder-based zeroth order optimization method for attacking black-box neural networks CC Tu, P Ting, PY Chen, S Liu, H Zhang, J Yi, CJ Hsieh, SM Cheng Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 742-749, 2019 | 228 | 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 | 154 | 2020 |
| Genattack: Practical black-box attacks with gradient-free optimization M Alzantot, Y Sharma, S Chakraborty, H Zhang, CJ Hsieh, MB Srivastava Proceedings of the Genetic and Evolutionary Computation Conference, 1111-1119, 2019 | 151 | 2019 |
| A convex relaxation barrier to tight robustness verification of neural networks H Salman, G Yang, H Zhang, CJ Hsieh, P Zhang Advances in Neural Information Processing Systems (NeurIPS), 9835-9846, 2019 | 151* | 2019 |
| Towards stable and efficient training of verifiably robust neural networks H Zhang, H Chen, C Xiao, S Gowal, R Stanforth, B Li, D Boning, CJ Hsieh International Conference on Learning Representations (ICLR) 2020, 2019 | 147 | 2019 |
| Attacking visual language grounding with adversarial examples: A case study on neural image captioning H Chen*, H Zhang*, PY Chen, J Yi, CJ Hsieh (*Equal Contribution) 56th Annual Meeting of the Association for …, 2017 | 136* | 2017 |
| 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, ... International Conference on Learning Representations (ICLR) 2019, 2018 | 125 | 2018 |
| Gradient boosted decision trees for high dimensional sparse output S Si, H Zhang, SS Keerthi, D Mahajan, IS Dhillon, CJ Hsieh International conference on machine learning, 3182-3190, 2017 | 108 | 2017 |
| The limitations of adversarial training and the blind-spot attack H Zhang*, H Chen*, Z Song, D Boning, IS Dhillon, CJ Hsieh (*Equal Contribution) International Conference on Learning Representations …, 2019 | 85 | 2019 |
Cho-Jui HsiehUniversity of California, Los AngelesVerified email at cs.ucla.edu
