| Unsupervised Feature Selection with Structured Graph Optimization XL Feiping Nie, Wei Zhu AAAI Conf. on Artificial Intelligence, 2016 | 315 | 2016 |
| Unsupervised large graph embedding F Nie, W Zhu, X Li Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017 | 162 | 2017 |
| Structured graph optimization for unsupervised feature selection F Nie, W Zhu, X Li IEEE Transactions on Knowledge and Data Engineering 33 (3), 1210-1222, 2019 | 83 | 2019 |
| Fast spectral clustering with efficient large graph construction W Zhu, F Nie, X Li 2017 IEEE international conference on acoustics, speech and signal …, 2017 | 76 | 2017 |
| Decision Tree SVM: An Extension of Linear SVM for Non-linear Classification F Nie, W Zhu, X Li Neurocomputing, 2019 | 57 | 2019 |
| Learning bias-invariant representation by cross-sample mutual information minimization W Zhu, H Zheng, H Liao, W Li, J Luo Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 36 | 2021 |
| Temperature network for few-shot learning with distribution-aware large-margin metric W Zhu, W Li, H Liao, J Luo Pattern Recognition 112, 2021 | 34 | 2021 |
| Personalized fashion recommendation from personal social media data: An item-to-set metric learning approach H Zheng, K Wu, JH Park, W Zhu, J Luo 2021 IEEE International Conference on Big Data (Big Data), 5014-5023, 2021 | 30 | 2021 |
| Unsupervised Large Graph Embedding Based on Balanced and Hierarchical K-means F Nie, W Zhu, X Li TKDE, 2020 | 29 | 2020 |
| Federated Learning of Molecular Properties with Graph Neural Networks in a Heterogeneous Setting W Zhu, A White, J Luo arXiv preprint arXiv:2109.07258, 2021 | 26 | 2021 |
| Localized adversarial domain generalization W Zhu, L Lu, J Xiao, M Han, J Luo, AP Harrison Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 25 | 2022 |
| Alleviating the Incompatibility between Cross Entropy Loss and Episode Training for Few-shot Skin Disease Classification W Zhu, H Liao, W Li, W Li, J Luo MICCAI, 2020 | 24 | 2020 |
| Federated medical image analysis with virtual sample synthesis W Zhu, J Luo International Conference on Medical Image Computing and Computer-Assisted …, 2022 | 9 | 2022 |
| Predicting Parkinson's Disease with Multimodal Irregularly Collected Longitudinal Smartphone Data W Li, W Zhu, ER Dorsey, J Luo 2020 IEEE International Conference on Data Mining (ICDM), 1106-1111, 2020 | 7 | 2020 |
| Deep federated anomaly detection for multivariate time series data W Zhu, D Song, Y Chen, W Cheng, B Zong, T Mizoguchi, C Lumezanu, ... 2022 IEEE International Conference on Big Data (Big Data), 1-10, 2022 | 5 | 2022 |
| SegPrompt: Using Segmentation Map as a Better Prompt to Finetune Deep Models for Kidney Stone Classification W Zhu, R Zhou, Y Yao, TD Campbell, RK Jain, J Luo Medical Imaging with Deep Learning, 1680-1690, 2024 | 4 | 2024 |
| Unifying Specialist Image Embedding into Universal Image Embedding Y Feng, F Peng, X Zhang, W Zhu, S Zhang, H Zhou, Z Li, T Duerig, ... arXiv preprint arXiv:2003.03701, 2020 | 4 | 2020 |
| Learning to Aggregate and Refine Noisy Labels for Visual Sentiment Analysis W Zhu, Z Zheng, H Zheng, H Lyu, J Luo 2022 26th International Conference on Pattern Recognition (ICPR), 571-577, 2022 | 1 | 2022 |
| Federated learning for anomaly detection D Song, Y Chen, C Lumezanu, T Mizoguchi, H Chen, W Zhu US Patent App. 17/395,118, 2022 | 1 | 2022 |
| Unsupervised anomaly detection by densely contrastive learning for time series data W Zhu, W Li, ER Dorsey, J Luo Neural Networks 168, 450-458, 2023 | | 2023 |
Jiebo LuoAlbert Arendt Hopeman Professor of Engineering, University of Rochester在 cs.rochester.edu 的电子邮件经过验证
