| A Theoretical Understanding of shallow Vision Transformers: Learning, Generalization, and Sample Complexity H Li, M Wang, S Liu, PY Chen International Conference on Learning Representations 2023, 2023 | 49 | 2023 |
| Generalization guarantee of training graph convolutional networks with graph topology sampling H Li, M Wang, S Liu, PY Chen, J Xiong International Conference on Machine Learning, 13014-13051, 2022 | 21 | 2022 |
| On the Convergence and Sample Complexity Analysis of Deep Q-Networks with -Greedy Exploration S Zhang, H Li, M Wang, M Liu, PY Chen, S Lu, S Liu, K Murugesan, ... neurips 2023, 2023 | 12 | 2023 |
| How Do Nonlinear Transformers Learn and Generalize in In-Context Learning? H Li, M Wang, S Lu, X Cui, PY Chen ICML 2024, 2024 | 9* | 2024 |
| Learning and generalization of one-hidden-layer neural networks, going beyond standard gaussian data H Li, S Zhang, M Wang 2022 56th Annual Conference on Information Sciences and Systems (CISS), 37-42, 2022 | 8 | 2022 |
| Transformers as Multi-Task Feature Selectors: Generalization Analysis of In-Context Learning H Li, M Wang, S Lu, H Wan, X Cui, PY Chen NeurIPS 2023 Workshop on Mathematics of Modern Machine Learning, 2023 | 7 | 2023 |
| What Improves the Generalization of Graph Transformer? A Theoretical Dive into Self-attention and Positional Encoding H Li, M Wang, T Ma, S Liu, Z Zhang, PY Chen ICML 2024, 2023 | 6 | 2023 |
| How does promoting the minority fraction affect generalization? A theoretical study of one-hidden-layer neural network on group imbalance H Li, S Zhang, Y Zhang, M Wang, S Liu, PY Chen IEEE Journal of Selected Topics in Signal Processing, 2024 | 5 | 2024 |
| Enhancing Graph Transformers with Hierarchical Distance Structural Encoding Y Luo, H Li, L Shi, XM Wu arXiv preprint arXiv:2308.11129, 2024 | 3* | 2024 |
| Learning on Transformers is Provable Low-Rank and Sparse: A One-layer Analysis H Li, M Wang, S Zhang, S Liu, PY Chen arXiv preprint arXiv:2406.17167, 2024 | | 2024 |
| How Do Nonlinear Transformers Acquire Generalization-Guaranteed CoT Ability? H Li, M Wang, S Lu, X Cui, PY Chen ICML 2024 Workshop on Theoretical Foundations of Foundation Models, 2024 | | 2024 |
| How Can Personalized Context Help? Exploring Joint Retrieval of Passage and Personalized Context H Wan, H Li, S Lu, X Cui, M Danilevsky ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and …, 2024 | | 2024 |
Pin-Yu ChenPrincipal Research Scientist, IBM Research AI; MIT-IBM Watson AI Lab; RPI-IBM AIRC在 ibm.com 的电子邮件经过验证
