| On the variance of the adaptive learning rate and beyond L Liu, H Jiang, P He, W Chen, X Liu, J Gao, J Han arXiv preprint arXiv:1908.03265, 2019 | 2190 | 2019 |
| SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization H Jiang, P He, W Chen, X Liu, J Gao, T Zhao arXiv preprint arXiv:1911.03437, 2019 | 460 | 2019 |
| Harnessing the power of llms in practice: A survey on chatgpt and beyond J Yang, H Jin, R Tang, X Han, Q Feng, H Jiang, S Zhong, B Yin, X Hu ACM Transactions on Knowledge Discovery from Data 18 (6), 1-32, 2024 | 407 | 2024 |
| Transformer hawkes process S Zuo, H Jiang, Z Li, T Zhao, H Zha International conference on machine learning, 11692-11702, 2020 | 287 | 2020 |
| Bond: Bert-assisted open-domain named entity recognition with distant supervision C Liang, Y Yu, H Jiang, S Er, R Wang, T Zhao, C Zhang Proceedings of the 26th ACM SIGKDD international conference on knowledge …, 2020 | 263 | 2020 |
| Fine-tuning pre-trained language model with weak supervision: A contrastive-regularized self-training approach Y Yu, S Zuo, H Jiang, W Ren, T Zhao, C Zhang arXiv preprint arXiv:2010.07835, 2020 | 119 | 2020 |
| Efficient approximation of deep relu networks for functions on low dimensional manifolds M Chen, H Jiang, W Liao, T Zhao Advances in neural information processing systems 32, 2019 | 116 | 2019 |
| Nonparametric regression on low-dimensional manifolds using deep ReLU networks: Function approximation and statistical recovery M Chen, H Jiang, W Liao, T Zhao Information and Inference: A Journal of the IMA 11 (4), 1203-1253, 2022 | 99 | 2022 |
| Condensing graphs via one-step gradient matching W Jin, X Tang, H Jiang, Z Li, D Zhang, J Tang, B Yin Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | 83 | 2022 |
| Calibrated language model fine-tuning for in-and out-of-distribution data L Kong, H Jiang, Y Zhuang, J Lyu, T Zhao, C Zhang arXiv preprint arXiv:2010.11506, 2020 | 75 | 2020 |
| Deep reinforcement learning with robust and smooth policy Q Shen, Y Li, H Jiang, Z Wang, T Zhao International Conference on Machine Learning, 8707-8718, 2020 | 74 | 2020 |
| huge: High-dimensional undirected graph estimation H Jiang, X Fei, H Liu, K Roeder, J Lafferty, L Wasserman, X Li, T Zhao R package version 1 (2), 2019 | 56 | 2019 |
| Super tickets in pre-trained language models: From model compression to improving generalization C Liang, S Zuo, M Chen, H Jiang, X Liu, P He, T Zhao, W Chen arXiv preprint arXiv:2105.12002, 2021 | 55 | 2021 |
| Named entity recognition with small strongly labeled and large weakly labeled data H Jiang, D Zhang, T Cao, B Yin, T Zhao arXiv preprint arXiv:2106.08977, 2021 | 45 | 2021 |
| Learning to defend by learning to attack H Jiang, Z Chen, Y Shi, B Dai, T Zhao International Conference on Artificial Intelligence and Statistics, 577-585, 2021 | 45* | 2021 |
| Multilingual knowledge graph completion with self-supervised adaptive graph alignment Z Huang, Z Li, H Jiang, T Cao, H Lu, B Yin, K Subbian, Y Sun, W Wang arXiv preprint arXiv:2203.14987, 2022 | 41 | 2022 |
| SEQZERO: Few-shot compositional semantic parsing with sequential prompts and zero-shot models J Yang, H Jiang, Q Yin, D Zhang, B Yin, D Yang arXiv preprint arXiv:2205.07381, 2022 | 39 | 2022 |
| Multi-domain neural machine translation with word-level adaptive layer-wise domain mixing H Jiang, C Liang, C Wang, T Zhao arXiv preprint arXiv:1911.02692, 2019 | 35 | 2019 |
| On computation and generalization of generative adversarial networks under spectrum control H Jiang, Z Chen, M Chen, F Liu, D Wang, T Zhao International Conference on Learning Representations, 2019 | 30* | 2019 |
| Picasso: A sparse learning library for high dimensional data analysis in R and Python J Ge, X Li, H Jiang, H Liu, T Zhang, M Wang, T Zhao Journal of Machine Learning Research 20 (44), 1-5, 2019 | 30* | 2019 |
Tuo ZhaoAssociate Professor, Georgia Tech在 gatech.edu 的电子邮件经过验证
