| Interpreting CNNs via Decision Trees Q Zhang, Y Yang, H Ma, YN Wu Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 424 | 2019 |
| Cleanclip: Mitigating data poisoning attacks in multimodal contrastive learning H Bansal, N Singhi, Y Yang, F Yin, A Grover, KW Chang Proceedings of the IEEE/CVF International Conference on Computer Vision, 112-123, 2023 | 50 | 2023 |
| Not All Poisons are Created Equal: Robust Training Against Data Poisoning Y Yang, TY Liu, B Mirzasoleiman International Conference on Machine Learning, 25154-25165, 2022 | 40 | 2022 |
| Mitigating Spurious Correlations in Multi-modal Models during Fine-tuning Y Yang, B Nushi, H Palangi, B Mirzasoleiman Proceedings of the 40th International Conference on Machine Learning 202 …, 2023 | 36 | 2023 |
| Enhancing fairness in face detection in computer vision systems by demographic bias mitigation Y Yang, A Gupta, J Feng, P Singhal, V Yadav, Y Wu, P Natarajan, ... Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society, 813-822, 2022 | 35 | 2022 |
| Unsupervised Learning of Neural Networks to Explain Neural Networks Q Zhang, Y Yang, Y Liu, YN Wu, SC Zhu arXiv preprint arXiv:1805.07468, 2018 | 34 | 2018 |
| Towards Sustainable Learning: Coresets for Data-efficient Deep Learning Y Yang, H Kang, B Mirzasoleiman Proceedings of the 40th International Conference on Machine Learning 202 …, 2023 | 29 | 2023 |
| Robust Learning with Progressive Data Expansion Against Spurious Correlation Y Deng*, Y Yang*, B Mirzasoleiman, Q Gu arXiv preprint arXiv:2306.04949, 2023 | 28 | 2023 |
| Friendly noise against adversarial noise: a powerful defense against data poisoning attack TY Liu, Y Yang, B Mirzasoleiman Advances in Neural Information Processing Systems 35, 11947-11959, 2022 | 23 | 2022 |
| Explaining deep convolutional neural networks via latent visual-semantic filter attention Y Yang, S Kim, J Joo Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 19 | 2022 |
| A Generative Model for Sampling High-performance and Diverse Weights for Neural Networks L Deutsch, E Nijkamp, Y Yang arXiv preprint arXiv:1905.02898, 2019 | 19 | 2019 |
| Data distillation can be like vodka: Distilling more times for better quality X Chen, Y Yang, Z Wang, B Mirzasoleiman arXiv preprint arXiv:2310.06982, 2023 | 18 | 2023 |
| SIEVE: Multimodal Dataset Pruning Using Image Captioning Models A Mahmoud, M Elhoushi, A Abbas, Y Yang, N Ardalani, H Leather, ... arXiv preprint arXiv:2310.02110, 2023 | 17 | 2023 |
| Visual Graph Mining for Graph Matching Q Zhang, X Song, Y Yang, H Ma, R Shibasaki Computer Vision and Image Understanding 178, 16-29, 2019 | 17 | 2019 |
| Ai risk categorization decoded (air 2024): From government regulations to corporate policies Y Zeng, K Klyman, A Zhou, Y Yang, M Pan, R Jia, D Song, P Liang, B Li arXiv preprint arXiv:2406.17864, 2024 | 16 | 2024 |
| Identifying spurious biases early in training through the lens of simplicity bias Y Yang, E Gan, GK Dziugaite, B Mirzasoleiman International Conference on Artificial Intelligence and Statistics, 2953-2961, 2024 | 16 | 2024 |
| Towards mitigating spurious correlations in the wild: A benchmark & a more realistic dataset S Joshi, Y Yang, Y Xue, W Yang, B Mirzasoleiman arXiv preprint arXiv:2306.11957, 2023 | 16 | 2023 |
| Eliminating spurious correlations from pre-trained models via data mixing Y Xue, A Payani, Y Yang, B Mirzasoleiman arXiv preprint arXiv:2305.14521, 2023 | 10 | 2023 |
| SmallToLarge (S2L): Scalable Data Selection for Fine-tuning Large Language Models by Summarizing Training Trajectories of Small Models Y Yang, S Mishra, JN Chiang, B Mirzasoleiman arXiv preprint arXiv:2403.07384, 2024 | 9 | 2024 |
| NeSSA: Near-Storage Data Selection for Accelerated Machine Learning Training N Prakriya, Y Yang, B Mirzasoleiman, CJ Hsieh, J Cong HotStorage '23: Proceedings of the 15th ACM Workshop on Hot Topics in …, 2023 | 9 | 2023 |
Baharan MirzasoleimanUCLAVerified email at cs.ucla.edu