| Zero-shot handwritten Chinese character recognition with hierarchical decomposition embedding Z Cao, J Lu, S Cui, C Zhang Pattern Recognition 107, 107488, 2020 | 102 | 2020 |
| Addressing Algorithmic Disparity and Performance Inconsistency in Federated Learning S Cui, W Pan, J Liang, C Zhang, F Wang Thirty-Fifth Conference on Neural Information Processing Systems, 2021 | 100 | 2021 |
| Explaining algorithmic fairness through fairness-aware causal path decomposition W Pan, S Cui, J Bian, C Zhang, F Wang Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021 | 42 | 2021 |
| Collaboration equilibrium in federated learning S Cui, J Liang, W Pan, K Chen, C Zhang, F Wang Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | 22 | 2022 |
| Correcting the user feedback-loop bias for recommendation systems W Pan, S Cui, H Wen, K Chen, C Zhang, F Wang arXiv preprint arXiv:2109.06037, 2021 | 20 | 2021 |
| Towards model-agnostic post-hoc adjustment for balancing ranking fairness and algorithm utility S Cui, W Pan, C Zhang, F Wang Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021 | 16* | 2021 |
| Accurate Forgetting for Heterogeneous Federated Continual Learning A Wuerkaixi, S Cui, J Zhang, K Yan, B Han, G Niu, L Fang, C Zhang, ... The Twelfth International Conference on Learning Representations, 2024 | 10 | 2024 |
| Synergy-of-experts: Collaborate to improve adversarial robustness S Cui, J Zhang, J Liang, B Han, M Sugiyama, C Zhang Advances in Neural Information Processing Systems 35, 32552-32567, 2022 | 6 | 2022 |
| Balancing Similarity and Complementarity for Federated Learning K Yan, S Cui, A Wuerkaixi, J Zhang, B Han, G Niu, M Sugiyama, C Zhang arXiv preprint arXiv:2405.09892, 2024 | 3 | 2024 |
| Bipartite ranking fairness through a model agnostic ordering adjustment S Cui, W Pan, C Zhang, F Wang IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023 | 3 | 2023 |
| Beyond Similarity: Personalized Federated Recommendation with Composite Aggregation H Zhang, H Li, J Chen, S Cui, K Yan, A Wuerkaixi, X Zhou, Z Shen, Y Li arXiv preprint arXiv:2406.03933, 2024 | 2 | 2024 |
| Unsupervised Disentanglement Learning by intervention W Pan, S Cui, C Zhang | 2 | 2020 |
| Decentralized federated learning via overlapping data augmentation S Cui, J Liang, W Pan, J Zhang, B Han, J Zhang, C Zhang, F Wang | 1 | 2023 |
| Dcr: Disentangled component representation for sketch generation Z Cao, S Cui, C Zhang Pattern Recognition Letters 145, 16-22, 2021 | 1 | 2021 |
| Fair and consistent federated learning S Cui, W Pan, J Liang, C Zhang, F Wang arXiv e-prints, arXiv: 2108.08435, 2021 | | 2021 |
| Learning to Collaborate S Cui, J Liang, W Pan, K Chen, C Zhang, F Wang | | 2021 |
| Neural Collapse Inspired Feature Alignment for Out-of-Distribution Generalization Z Chen, M Zhang, S Cui, H Li, G Niu, M Gong, C Zhang, K Zhang The Thirty-eighth Annual Conference on Neural Information Processing Systems, 0 | | |
| CLAP: Collaborative Adaptation for Patchwork Learning S Cui, A Wuerkaixi, W Pan, J Liang, L Fang, C Zhang, F Wang The Twelfth International Conference on Learning Representations, 0 | | |
| Precision Collaboration for Federated Learning S Cui, A Wuerkaixi, J Liang, W Pan, J Zhang, C Zhang, F Wang | | |
| Collaborate to Defend Against Adversarial Attacks S Cui, J Zhang, J Liang, M Sugiyama, C Zhang | | |
Fei Wang, FAMIA, FIAHSI, FACMIProfessor at Cornell UniversityAdresse e-mail validée de med.cornell.edu