| Revisiting and Advancing Fast Adversarial Training Through The Lens of Bi-Level Optimization Y Zhang, G Zhang, P Khanduri, M Hong, S Chang, S Liu Proceedings of the 39th International Conference on Machine Learning, 26693 …, 2022 | 69 | 2022 |
| Understanding and improving visual prompting: A label-mapping perspective A Chen, Y Yao, PY Chen, Y Zhang, S Liu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 43 | 2023 |
| A pilot study of query-free adversarial attack against stable diffusion H Zhuang, Y Zhang, S Liu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 36 | 2023 |
| 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 (NeurIPS), 2022 | 34 | 2022 |
| Fairness Reprogramming G Zhang, Y Zhang, Y Zhang, W Fan, Q Li, S Liu, S Chang Advances in Neural Information Processing Systems (NeurIPS), 2022 | 34 | 2022 |
| Quarantine: Sparsity can uncover the trojan attack trigger for free T Chen, Z Zhang, Y Zhang, S Chang, S Liu, Z Wang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 24 | 2022 |
| Salun: Empowering machine unlearning via gradient-based weight saliency in both image classification and generation C Fan, J Liu, Y Zhang, D Wei, E Wong, S Liu arXiv preprint arXiv:2310.12508, 2023 | 18 | 2023 |
| Textgrad: Advancing robustness evaluation in nlp by gradient-driven optimization B Hou, J Jia, Y Zhang, G Zhang, Y Zhang, S Liu, S Chang arXiv preprint arXiv:2212.09254, 2022 | 15 | 2022 |
| An Introduction to Bilevel Optimization: Foundations and applications in signal processing and machine learning Y Zhang, P Khanduri, I Tsaknakis, Y Yao, M Hong, S Liu IEEE Signal Processing Magazine 41 (1), 38-59, 2024 | 12 | 2024 |
| To generate or not? safety-driven unlearned diffusion models are still easy to generate unsafe images... for now Y Zhang, J Jia, X Chen, A Chen, Y Zhang, J Liu, K Ding, S Liu arXiv preprint arXiv:2310.11868, 2023 | 12 | 2023 |
| Distributed Adversarial Training to Robustify Deep Neural Networks at Scale G Zhang, S Lu, Y Zhang, X Chen, PY Chen, L Martie, L Horesh, M Hong, ... | 10 | 2022 |
| Linearly constrained bilevel optimization: A smoothed implicit gradient approach P Khanduri, I Tsaknakis, Y Zhang, J Liu, S Liu, J Zhang, M Hong International Conference on Machine Learning, 16291-16325, 2023 | 8 | 2023 |
| Deepzero: Scaling up zeroth-order optimization for deep model training A Chen, Y Zhang, J Jia, J Diffenderfer, J Liu, K Parasyris, Y Zhang, ... arXiv preprint arXiv:2310.02025, 2023 | 6 | 2023 |
| What Is Missing in IRM Training and Evaluation? Challenges and Solutions Y Zhang, P Sharma, P Ram, M Hong, K Varshney, S Liu The Eleventh International Conference on Learning Representations (ICLR 2023), 2023 | 5 | 2023 |
| Robust Mixture-of-Expert Training for Convolutional Neural Networks Y Zhang, R Cai, T Chen, G Zhang, H Zhang, PY Chen, S Chang, Z Wang, ... Proceedings of the IEEE/CVF International Conference on Computer Vision, 90-101, 2023 | 4 | 2023 |
| How does promoting the minority fraction affect generalization? A theoretical study of one-hidden-layer neural network on group imbalance H Li, S Zhang, Y Zhang, M Wang, S Liu, PY Chen IEEE Journal of Selected Topics in Signal Processing, 2024 | 3 | 2024 |
| UnlearnCanvas: A Stylized Image Dataset to Benchmark Machine Unlearning for Diffusion Models Y Zhang, Y Zhang, Y Yao, J Jia, J Liu, X Liu, S Liu arXiv preprint arXiv:2402.11846, 2024 | 3 | 2024 |
| Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark Y Zhang, P Li, J Hong, J Li, Y Zhang, W Zheng, PY Chen, JD Lee, W Yin, ... arXiv preprint arXiv:2402.11592, 2024 | 3 | 2024 |
| Soul: Unlocking the power of second-order optimization for llm unlearning J Jia, Y Zhang, Y Zhang, J Liu, B Runwal, J Diffenderfer, B Kailkhura, ... arXiv preprint arXiv:2404.18239, 2024 | 2 | 2024 |
| Selectivity Drives Productivity: Efficient Dataset Pruning for Enhanced Transfer Learning Y Zhang, Y Zhang, A Chen, J Liu, G Liu, M Hong, S Chang, S Liu Advances in Neural Information Processing Systems 36, 2024 | 2 | 2024 |
Sijia LiuMichigan State University & MIT-IBM Watson AI Lab在 msu.edu 的电子邮件经过验证
