Federated learning from pre-trained models: A contrastive learning approach Y Tan, G Long, J Ma, L Liu, T Zhou, J Jiang Advances in neural information processing systems 35, 19332-19344, 2022 | 187 | 2022 |
On the convergence of clustered federated learning J Ma, G Long, T Zhou, J Jiang, C Zhang arXiv preprint arXiv:2202.06187, 2022 | 57 | 2022 |
DeepMMSA: A novel multimodal deep learning method for non-small cell lung cancer survival analysis Y Wu, J Ma, X Huang, SH Ling, SW Su 2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2021 | 30 | 2021 |
Pareto policy pool for model-based offline reinforcement learning Y Yang, J Jiang, T Zhou, J Ma, Y Shi International Conference on Learning Representations, 2021 | 22 | 2021 |
Structured federated learning through clustered additive modeling J Ma, T Zhou, G Long, J Jiang, C Zhang Advances in Neural Information Processing Systems 36, 43097-43107, 2023 | 13 | 2023 |
Personalized Federated Learning with Robust Clustering against Model Poisoning J Ma, M Xie, G Long ADMA 2022, 0 | 6* | |
Robust Clustered Federated Learning with Bootstrap Median-of-Means M Xie, J MA, G Long, C Zhang APWEB-WAIM 2022, 0 | 2* | |
Multi-level additive modeling for structured non-iid federated learning S Chen, T Zhou, G Long, J Ma, J Jiang, C Zhang arXiv preprint arXiv:2405.16472, 2024 | 1 | 2024 |
Clustered Federated Learning J Ma PQDT-Global, 2023 | | 2023 |
FedPCL: Learning to Blend Representations for Federated Prototype Learning G Long, J Ma, J Jiang, L Liu, T Zhou, Y Tan | | 2022 |