| Gradient descent finds global minima of deep neural networks S Du, J Lee, H Li, L Wang, X Zhai International conference on machine learning, 1675-1685, 2019 | 1460 | 2019 |
| The expressive power of neural networks: A view from the width Z Lu, H Pu, F Wang, Z Hu, L Wang Advances in neural information processing systems 30, 2017 | 1323 | 2017 |
| Reppoints: Point set representation for object detection Z Yang, S Liu, H Hu, L Wang, S Lin Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 1241 | 2019 |
| On layer normalization in the transformer architecture R Xiong, Y Yang, D He, K Zheng, S Zheng, C Xing, H Zhang, Y Lan, ... International conference on machine learning, 10524-10533, 2020 | 1191 | 2020 |
| Dual learning for machine translation D He, Y Xia, T Qin, L Wang, N Yu, TY Liu, WY Ma Advances in neural information processing systems 29, 2016 | 1089 | 2016 |
| On the Euclidean distance of images L Wang, Y Zhang, J Feng IEEE transactions on pattern analysis and machine intelligence 27 (8), 1334-1339, 2005 | 889 | 2005 |
| A theoretical analysis of NDCG type ranking measures Y Wang, L Wang, Y Li, D He, TY Liu Conference on learning theory, 25-54, 2013 | 789 | 2013 |
| Nesterov accelerated gradient and scale invariance for adversarial attacks J Lin, C Song, K He, L Wang, JE Hopcroft arXiv preprint arXiv:1908.06281, 2019 | 693 | 2019 |
| Learning to navigate for fine-grained classification Z Yang, T Luo, D Wang, Z Hu, J Gao, L Wang Proceedings of the European conference on computer vision (ECCV), 420-435, 2018 | 674 | 2018 |
| Accurate pulmonary nodule detection in computed tomography images using deep convolutional neural networks J Ding, A Li, Z Hu, L Wang International conference on medical image computing and computer-assisted …, 2017 | 460 | 2017 |
| Memory enhanced global-local aggregation for video object detection Y Chen, Y Cao, H Hu, L Wang Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 373 | 2020 |
| Representation degeneration problem in training natural language generation models J Gao, D He, X Tan, T Qin, L Wang, TY Liu arXiv preprint arXiv:1907.12009, 2019 | 300 | 2019 |
| Boosting few-shot learning with adaptive margin loss A Li, W Huang, X Lan, J Feng, Z Li, L Wang Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 239 | 2020 |
| Towards revealing the mystery behind chain of thought: a theoretical perspective G Feng, B Zhang, Y Gu, H Ye, D He, L Wang Advances in Neural Information Processing Systems 36, 70757-70798, 2023 | 226 | 2023 |
| Dense relation distillation with context-aware aggregation for few-shot object detection H Hu, S Bai, A Li, J Cui, L Wang Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 226 | 2021 |
| Learning relationships for multi-view 3D object recognition Z Yang, L Wang Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 222 | 2019 |
| Graphnorm: A principled approach to accelerating graph neural network training T Cai, S Luo, K Xu, D He, T Liu, L Wang International Conference on Machine Learning, 1204-1215, 2021 | 217 | 2021 |
| Understanding and improving transformer from a multi-particle dynamic system point of view Y Lu, Z Li, D He, Z Sun, B Dong, T Qin, L Wang, TY Liu arXiv preprint arXiv:1906.02762, 2019 | 217 | 2019 |
| Visual autoregressive modeling: Scalable image generation via next-scale prediction K Tian, Y Jiang, Z Yuan, B Peng, L Wang Advances in neural information processing systems 37, 84839-84865, 2024 | 209 | 2024 |
| On the depth of deep neural networks: A theoretical view S Sun, W Chen, L Wang, X Liu, TY Liu Proceedings of the AAAI Conference on Artificial Intelligence 30 (1), 2016 | 209 | 2016 |
Di HePeking University確認したメール アドレス: pku.edu.cn