| Large batch optimization for deep learning: Training bert in 76 minutes Y You, J Li, S Reddi, J Hseu, S Kumar, S Bhojanapalli, X Song, J Demmel, ... arXiv preprint arXiv:1904.00962, 2019 | 1065 | 2019 |
| Large batch training of convolutional networks Y You, I Gitman, B Ginsburg arXiv preprint arXiv:1708.03888, 2017 | 890 | 2017 |
| Imagenet training in minutes Y You, Z Zhang, CJ Hsieh, J Demmel, K Keutzer Proceedings of the 47th international conference on parallel processing, 1-10, 2018 | 506 | 2018 |
| Scaling sgd batch size to 32k for imagenet training Y You, I Gitman, B Ginsburg arXiv preprint arXiv:1708.03888 6 (12), 6, 2017 | 419 | 2017 |
| Cafe: Learning to condense dataset by aligning features K Wang, B Zhao, X Peng, Z Zhu, S Yang, S Wang, G Huang, H Bilen, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 228 | 2022 |
| Towards efficient and scalable sharpness-aware minimization Y Liu, S Mai, X Chen, CJ Hsieh, Y You Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 139 | 2022 |
| Colossal-ai: A unified deep learning system for large-scale parallel training S Li, H Liu, Z Bian, J Fang, H Huang, Y Liu, B Wang, Y You Proceedings of the 52nd International Conference on Parallel Processing, 766-775, 2023 | 124 | 2023 |
| Crafting better contrastive views for siamese representation learning X Peng, K Wang, Z Zhu, M Wang, Y You Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 120 | 2022 |
| Reducing BERT pre-training time from 3 days to 76 minutes Y You, J Li, J Hseu, X Song, J Demmel, CJ Hsieh arXiv preprint arXiv:1904.00962 12, 2, 2019 | 114 | 2019 |
| Large-batch training for LSTM and beyond Y You, J Hseu, C Ying, J Demmel, K Keutzer, CJ Hsieh Proceedings of the International Conference for High Performance Computing …, 2019 | 106 | 2019 |
| Scaling deep learning on GPU and knights landing clusters Y You, A Buluç, J Demmel Proceedings of the International Conference for High Performance Computing …, 2017 | 101 | 2017 |
| Go wider instead of deeper F Xue, Z Shi, F Wei, Y Lou, Y Liu, Y You Proceedings of the AAAI Conference on Artificial Intelligence 36 (8), 8779-8787, 2022 | 79 | 2022 |
| 100-epoch imagenet training with alexnet in 24 minutes Y You, Z Zhang, C Hsieh, J Demmel, K Keutzer arXiv preprint arXiv:1709.05011 8, 2017 | 78 | 2017 |
| Dream: Efficient dataset distillation by representative matching Y Liu, J Gu, K Wang, Z Zhu, W Jiang, Y You Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 66 | 2023 |
| Fast deep neural network training on distributed systems and cloud TPUs Y You, Z Zhang, CJ Hsieh, J Demmel, K Keutzer IEEE Transactions on Parallel and Distributed Systems 30 (11), 2449-2462, 2019 | 66 | 2019 |
| Preventing zero-shot transfer degradation in continual learning of vision-language models Z Zheng, M Ma, K Wang, Z Qin, X Yue, Y You Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 65 | 2023 |
| To repeat or not to repeat: Insights from scaling llm under token-crisis F Xue, Y Fu, W Zhou, Z Zheng, Y You Advances in Neural Information Processing Systems 36, 2024 | 59 | 2024 |
| Sequence parallelism: Long sequence training from system perspective S Li, F Xue, C Baranwal, Y Li, Y You arXiv preprint arXiv:2105.13120, 2021 | 56 | 2021 |
| Prompt vision transformer for domain generalization Z Zheng, X Yue, K Wang, Y You arXiv preprint arXiv:2208.08914, 2022 | 54 | 2022 |
| Asynchronous parallel greedy coordinate descent Y You, X Lian, J Liu, HF Yu, IS Dhillon, J Demmel, CJ Hsieh Advances in Neural Information Processing Systems, 4682-4690, 2016 | 53 | 2016 |
