| Lightgbm: A highly efficient gradient boosting decision tree G Ke, Q Meng, T Finley, T Wang, W Chen, W Ma, Q Ye, TY Liu Advances in neural information processing systems 30, 2017 | 12246 | 2017 |
| R-drop: Regularized dropout for neural networks L Wu, J Li, Y Wang, Q Meng, T Qin, W Chen, M Zhang, TY Liu Advances in Neural Information Processing Systems 34, 10890-10905, 2021 | 377 | 2021 |
| Asynchronous stochastic gradient descent with delay compensation S Zheng, Q Meng, T Wang, W Chen, N Yu, ZM Ma, TY Liu International conference on machine learning, 4120-4129, 2017 | 304 | 2017 |
| A communication-efficient parallel algorithm for decision tree Q Meng, G Ke, T Wang, W Chen, Q Ye, ZM Ma, TY Liu Advances in Neural Information Processing Systems 29, 2016 | 152 | 2016 |
| Convergence analysis of distributed stochastic gradient descent with shuffling Q Meng, W Chen, Y Wang, ZM Ma, TY Liu Neurocomputing 337, 46-57, 2019 | 139 | 2019 |
| Priorgrad: Improving conditional denoising diffusion models with data-dependent adaptive prior S Lee, H Kim, C Shin, X Tan, C Liu, Q Meng, T Qin, W Chen, S Yoon, ... arXiv preprint arXiv:2106.06406, 2021 | 89 | 2021 |
| An efficient Lorentz equivariant graph neural network for jet tagging S Gong, Q Meng, J Zhang, H Qu, C Li, S Qian, W Du, ZM Ma, TY Liu Journal of High Energy Physics 2022 (7), 1-22, 2022 | 81 | 2022 |
| Target transfer Q-learning and its convergence analysis Y Wang, Y Liu, W Chen, ZM Ma, TY Liu Neurocomputing 392, 11-22, 2020 | 54 | 2020 |
| SE (3) equivariant graph neural networks with complete local frames W Du, H Zhang, Y Du, Q Meng, W Chen, N Zheng, B Shao, TY Liu International Conference on Machine Learning, 5583-5608, 2022 | 45 | 2022 |
| Reinforcement learning with dynamic boltzmann softmax updates L Pan, Q Cai, Q Meng, W Chen, L Huang, TY Liu arXiv preprint arXiv:1903.05926, 2019 | 45 | 2019 |
| The implicit bias for adaptive optimization algorithms on homogeneous neural networks B Wang, Q Meng, W Chen, TY Liu International Conference on Machine Learning, 10849-10858, 2021 | 31 | 2021 |
| -SGD: Optimizing ReLU Neural Networks in its Positively Scale-Invariant Space Q Meng, S Zheng, H Zhang, W Chen, ZM Ma, TY Liu arXiv preprint arXiv:1802.03713, 2018 | 30 | 2018 |
| Machine-learning nonconservative dynamics for new-physics detection Z Liu, B Wang, Q Meng, W Chen, M Tegmark, TY Liu Physical Review E 104 (5), 055302, 2021 | 26 | 2021 |
| Unidrop: A simple yet effective technique to improve transformer without extra cost Z Wu, L Wu, Q Meng, Y Xia, S Xie, T Qin, X Dai, TY Liu arXiv preprint arXiv:2104.04946, 2021 | 25 | 2021 |
| Asynchronous Accelerated Stochastic Gradient Descent. Q Meng, W Chen, J Yu, T Wang, Z Ma, TY Liu IJCAI, 1853-1859, 2016 | 25 | 2016 |
| Capacity control of ReLU neural networks by basis-path norm S Zheng, Q Meng, H Zhang, W Chen, N Yu, TY Liu Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 5925-5932, 2019 | 24 | 2019 |
| Asynchronous stochastic proximal optimization algorithms with variance reduction Q Meng, W Chen, J Yu, T Wang, ZM Ma, TY Liu Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017 | 24 | 2017 |
| Positively scale-invariant flatness of relu neural networks M Yi, Q Meng, W Chen, Z Ma, TY Liu arXiv preprint arXiv:1903.02237, 2019 | 23 | 2019 |
| The impact of large language models on scientific discovery: a preliminary study using gpt-4 MR AI4Science, MA Quantum arXiv preprint arXiv:2311.07361, 2023 | 17 | 2023 |
| Dynamic of stochastic gradient descent with state-dependent noise Q Meng, S Gong, W Chen, ZM Ma, TY Liu arXiv preprint arXiv:2006.13719, 2020 | 14 | 2020 |
Tie-Yan LiuDistinguished Scientist, Microsoft Research AI4Science | IEEE Fellow | ACM Fellow | AAIA Fellow在 microsoft.com 的电子邮件经过验证
