| A comprehensive survey on pretrained foundation models: A history from bert to chatgpt C Zhou, Q Li, C Li, J Yu, Y Liu, G Wang, K Zhang, C Ji, Q Yan, L He, ... International Journal of Machine Learning and Cybernetics, 1-65, 2024 | 712* | 2024 |
| A survey on text classification: From traditional to deep learning Q Li, H Peng, J Li, C Xia, R Yang, L Sun, PS Yu, L He ACM Transactions on Intelligent Systems and Technology (TIST) 13 (2), 1-41, 2022 | 709* | 2022 |
| Adversarial Attack and Defense on Graph Data: A Survey L Sun, Y Dou, Y Carl, J Wang, PS Yu, L He, B Li IEEE Transactions on Knowledge and Data Engineering, 2018 | 382* | 2018 |
| Position: TrustLLM: Trustworthiness in large language models Y Huang, L Sun, H Wang, S Wu, Q Zhang, Y Li, C Gao, Y Huang, W Lyu, ... International Conference on Machine Learning (ICML), 20166-20270, 2024 | 355* | 2024 |
| Multiple Incomplete Views Clustering via Weighted Nonnegative Matrix Factorization with Regularization W Shao, L He, SY Philip Joint European Conference on Machine Learning and Knowledge Discovery in …, 2015 | 326 | 2015 |
| Multi-level Feature Learning for Contrastive Multi-view Clustering J Xu, H Tang, Y Ren, L Peng, X Zhu, L He IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022 | 286 | 2022 |
| Sora: A review on background, technology, limitations, and opportunities of large vision models Y Liu, K Zhang, Y Li, Z Yan, C Gao, R Chen, Z Yuan, Y Huang, H Sun, ... arXiv preprint arXiv:2402.17177, 2024 | 266 | 2024 |
| Fedgraphnn: A federated learning system and benchmark for graph neural networks C He, K Balasubramanian, E Ceyani, C Yang, H Xie, L Sun, L He, L Yang, ... arXiv preprint arXiv:2104.07145, 2021 | 256 | 2021 |
| KG-BART: Knowledge Graph-Augmented BART for Generative Commonsense Reasoning Y Liu, Y Wan, L He, H Peng, PS Yu Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI), 2021 | 228 | 2021 |
| BiomedGPT: A Generalist Vision-Language Foundation Model for Diverse Biomedical Tasks K Zhang, R Zhou, E Adhikarla, Z Yan, Y Liu, J Yu, Z Liu, X Chen, ... Nature Medicine, 1-13, 2024 | 216* | 2024 |
| SUGAR: Subgraph Neural Network with Reinforcement Pooling and Self-Supervised Mutual Information Mechanism Q Sun, H Peng, J Li, Y Ning, J Wu, PS Yu, L He International World Wide Web Conference (WWW), 2021 | 201 | 2021 |
| Dynamic Graph Convolutional Network for Long-Term Traffic Flow Prediction with Reinforcement Learning H Peng, B Du, M Liu, M Liu, S Ji, S Wang, X Zhang, L He Information Sciences, 2021 | 199 | 2021 |
| Hierarchical Taxonomy-Aware and Attentional Graph Capsule RCNNs for Large-Scale Multi-Label Text Classification H Peng, J Li, S Wang, L Wang, Q Gong, R Yang, B Li, PS Yu, L He IEEE Transactions on Knowledge and Data Engineering (TKDE), 2019 | 187 | 2019 |
| Mixup-Transfomer: Dynamic Data Augmentation for NLP Tasks L Sun, C Xia, W Yin, T Liang, PS Yu, L He International Conference on Computational Linguistics (COLING), 2020 | 176 | 2020 |
| Self-supervised discriminative feature learning for deep multi-view clustering J Xu, Y Ren, H Tang, Z Yang, L Pan, Y Yang, X Pu, PS Yu, L He IEEE Transactions on Knowledge and Data Engineering 35 (7), 7470-7482, 2022 | 168 | 2022 |
| BrainGB: A Benchmark for Brain Network Analysis with Graph Neural Networks H Cui, W Dai, Y Zhu, X Kan, AAC Gu, J Lukemire, L Zhan, L He, Y Guo, ... IEEE Transactions on Medical Imaging (TMI), 2023 | 157 | 2023 |
| Multi-VAE: Learning Disentangled View-common and View-peculiar Visual Representations for Multi-view Clustering J Xu, Y Ren, H Tang, X Pu, X Zhu, M Zeng, L He International Conference on Computer Vision (ICCV), 2021 | 155 | 2021 |
| Deep clustering: A comprehensive survey Y Ren, J Pu, Z Yang, J Xu, G Li, X Pu, PS Yu, L He IEEE transactions on neural networks and learning systems, 2024 | 154 | 2024 |
| A Robust Least Squares Support Vector Machine for Regression and Classification with Outliers or Noises X Yang, L Tan, L He Neurocomputing, 2014 | 149 | 2014 |
| Deep Learning for Drug Repurposing: Methods, Databases, and Applications X Pan, X Lin, D Cao, X Zeng, PS Yu, L He, R Nussinov, F Cheng WIREs Computational Molecular Science, 2021 | 147 | 2021 |
Philip S. YuProfessor of Computer Science, University of Illinons at Chicago在 cs.uic.edu 的电子邮件经过验证
