| Explaining knowledge distillation by quantifying the knowledge X Cheng, Z Rao, Y Chen, Q Zhang Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 127 | 2020 |
| Quantifying the knowledge in a DNN to explain knowledge distillation for classification Q Zhang, X Cheng, Y Chen, Z Rao IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (4), 5099-5113, 2022 | 22 | 2022 |
| On the Equivalence between Neural Network and Support Vector Machine Y Chen, W Huang, LM Nguyen, TW Weng 35th Conference on Neural Information Processing Systems (NeurIPS 2021), 2021 | 17 | 2021 |
| Analyzing deep pac-bayesian learning with neural tangent kernel: Convergence, analytic generalization bound, and efficient hyperparameter selection W Huang, C Liu, Y Chen, RY Da Xu, M Zhang, TW Weng Transactions on Machine Learning Research, 2023 | 7* | 2023 |
| Cross-Task Linearity Emerges in the Pretraining-Finetuning Paradigm Z Zhou, Z Chen, Y Chen, B Zhang, J Yan arXiv preprint arXiv:2402.03660, 2024 | | 2024 |
| Analyzing Generalization of Neural Networks through Loss Path Kernels Y Chen, W Huang, H Wang, C Loh, A Srivastava, LM Nguyen, TW Weng Thirty-seventh Conference on Neural Information Processing Systems, 2023 | | 2023 |
| The Importance of Prompt Tuning for Automated Neuron Explanations J Lee, T Oikarinen, A Chantha, KC Chang, Y Chen, TW Weng arXiv preprint arXiv:2310.06200, 2023 | | 2023 |
Quanshi ZhangShanghai Jiao Tong UniversityVerified email at sjtu.edu.cn
