| Rethinking the Value of Network Pruning Z Liu*, M Sun*, T Zhou, G Huang, T Darrell International Conference on Learning Representations (ICLR) 2019, 2019 | 1464 | 2019 |
| Denoised Smoothing: A Provable Defense for Pretrained Classifiers H Salman, M Sun, G Yang, A Kapoor, JZ Kolter Advances in Neural Information Processing Systems 33, 21945-21957, 2020 | 112* | 2020 |
| Data poisoning attack against unsupervised node embedding methods M Sun, J Tang, H Li, B Li, C Xiao, Y Chen, D Song arXiv preprint arXiv:1810.12881, 2018 | 77 | 2018 |
| Characterizing attacks on deep reinforcement learning X Pan, C Xiao, W He, S Yang, J Peng, M Sun, J Yi, Z Yang, M Liu, B Li, ... arXiv preprint arXiv:1907.09470, 2019 | 66 | 2019 |
| Test-Time Adaptation via Conjugate Pseudo-Labels S Goyal*, M Sun*, A Raghunathan, JZ Kolter Advances in Neural Information Processing Systems (NeurIPS) 2022, 2022 | 32 | 2022 |
| A Simple and Effective Pruning Approach for Large Language Models M Sun*, Z Liu*, A Bair, JZ Kolter arXiv preprint arXiv:2306.11695, 2023 | 27 | 2023 |
| Poisoned classifiers are not only backdoored, they are fundamentally broken M Sun, S Agarwal, JZ Kolter arXiv preprint arXiv:2010.09080, 2020 | 19 | 2020 |
| Can shape structure features improve model robustness under diverse adversarial settings? M Sun, Z Li, C Xiao, H Qiu, B Kailkhura, M Liu, B Li Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 18 | 2021 |
| (Certified!!) Adversarial Robustness for Free! N Carlini, F Tramer, K Dj Dvijotham, L Rice, M Sun, JZ Kolter International Conference on Learning Representations (ICLR), 2023 | 4 | 2023 |
| Single Image Backdoor Inversion via Robust Smoothed Classifiers M Sun, JZ Kolter Computer Vision and Pattern Recognition (CVPR) 2023, 2023 | 2 | 2023 |
| Reliable Test-Time Adaptation via Agreement-on-the-Line E Kim, M Sun, A Raghunathan, Z Kolter arXiv preprint arXiv:2310.04941, 2023 | | 2023 |
Zico KolterCarnegie Mellon UniversityVerified email at cs.cmu.edu
