| Empirical evaluation of rectified activations in convolutional network B Xu arXiv preprint arXiv:1505.00853, 2015 | 4222 | 2015 |
| Mxnet: A flexible and efficient machine learning library for heterogeneous distributed systems T Chen, M Li, Y Li, M Lin, N Wang, M Wang, T Xiao, B Xu, C Zhang, ... arXiv preprint arXiv:1512.01274, 2015 | 2909 | 2015 |
| Scaling distributed machine learning with the parameter server M Li, DG Andersen, JW Park, AJ Smola, A Ahmed, V Josifovski, J Long, ... 11th USENIX Symposium on operating systems design and implementation (OSDI …, 2014 | 2295 | 2014 |
| Resnest: Split-attention networks H Zhang, C Wu, Z Zhang, Y Zhu, H Lin, Z Zhang, Y Sun, T He, J Mueller, ... Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 1985 | 2022 |
| Bag of tricks for image classification with convolutional neural networks T He, Z Zhang, H Zhang, Z Zhang, J Xie, M Li Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 1868 | 2019 |
| Dive into deep learning A Zhang, ZC Lipton, M Li, AJ Smola arXiv preprint arXiv:2106.11342, 2021 | 1627 | 2021 |
| Efficient mini-batch training for stochastic optimization M Li, T Zhang, Y Chen, AJ Smola Proceedings of the 20th ACM SIGKDD international conference on Knowledge …, 2014 | 1054 | 2014 |
| Autogluon-tabular: Robust and accurate automl for structured data N Erickson, J Mueller, A Shirkov, H Zhang, P Larroy, M Li, A Smola arXiv preprint arXiv:2003.06505, 2020 | 751 | 2020 |
| Communication efficient distributed machine learning with the parameter server M Li, DG Andersen, AJ Smola, K Yu Advances in Neural Information Processing Systems 27, 2014 | 744 | 2014 |
| Automatic chain of thought prompting in large language models Z Zhang, A Zhang, M Li, A Smola arXiv preprint arXiv:2210.03493, 2022 | 710 | 2022 |
| Emotion classification based on gamma-band EEG M Li, BL Lu 2009 Annual International Conference of the IEEE Engineering in medicine and …, 2009 | 564 | 2009 |
| Multimodal chain-of-thought reasoning in language models Z Zhang, A Zhang, M Li, H Zhao, G Karypis, A Smola arXiv preprint arXiv:2302.00923, 2023 | 339 | 2023 |
| Parameter Server for Distributed Machine Learning M Li, L Zhou, Z Yang, A Li, F Xia, DG Andersen, A Smola | 293 | 2013 |
| Bag of freebies for training object detection neural networks Z Zhang, T He, H Zhang, Z Zhang, J Xie, M Li arXiv preprint arXiv:1902.04103, 2019 | 238 | 2019 |
| Gluoncv and gluonnlp: Deep learning in computer vision and natural language processing J Guo, H He, T He, L Lausen, M Li, H Lin, X Shi, C Wang, J Xie, S Zha, ... Journal of Machine Learning Research 21 (23), 1-7, 2020 | 235 | 2020 |
| A comprehensive study of deep video action recognition Y Zhu, X Li, C Liu, M Zolfaghari, Y Xiong, C Wu, Z Zhang, J Tighe, ... arXiv preprint arXiv:2012.06567, 2020 | 224 | 2020 |
| XGBoost: Extreme gradient boosting, 2021 T Chen, T He, M Benesty, V Khotilovich, Y Tang, H Cho, K Chen, ... R package version 1 (1.1), 2021 | 193 | 2021 |
| xgboost: extreme gradient boosting. R package version 0.71. 2 T Chen, T He, M Benesty, V Khotilovich, Y Tang, H Cho, K Chen, ... Grin Verlag: München, Germnay, 2018 | 188 | 2018 |
| Optimizing {CNN} model inference on {CPUs} Y Liu, Y Wang, R Yu, M Li, V Sharma, Y Wang 2019 USENIX Annual Technical Conference (USENIX ATC 19), 1025-1040, 2019 | 182 | 2019 |
| Making large-scale Nyström approximation possible M Li, JTY Kwok, B Lü Proceedings of the 27th International Conference on Machine Learning, ICML …, 2010 | 168 | 2010 |