Loss-based differentiation strategy for privacy preserving of social robots. - Qinglin Yang; Taiyu Wang; Kaiming Zhu; Junbo Wang 001; Yu Han; Chunhua Su (J. Supercomput., 2023)

Correction to: Loss-based differentiation strategy for privacy preserving of social robots. - Qinglin Yang; Taiyu Wang; Kaiming Zhu; Junbo Wang 001; Yu Han; Chunhua Su (J. Supercomput., 2023)

Collaborative Machine Learning: Schemes, Robustness, and Privacy. - Junbo Wang 001; Amitangshu Pal; Qinglin Yang; Krishna Kant 001; Kaiming Zhu; Song Guo 001 (IEEE Trans. Neural Networks Learn. Syst., 2023)

FedSD: Cross-Heterogeneous Federated Learning Based on Self-distillation. - Haiwen Chen; Songcan Yu; Shupeng Zhao; Junbo Wang 001; Kaiming Zhu; Kento Sato (PRICAI (2), 2024)

LDS-FL: Loss Differential Strategy Based Federated Learning for Privacy Preserving. - Taiyu Wang; Qinglin Yang; Kaiming Zhu; Junbo Wang 001; Chunhua Su; Kento Sato (IEEE Trans. Inf. Forensics Secur., 2024)

Spatial-Spectral Total Variation-Regularized Low-Rank Tensor Representation for Hyperspectral Anomaly Detection. - ZhiGuo Du; Xingyu Chen; Minghao Jia; Xiaoying Qiu; Zelong Chen; Kaiming Zhu (J. Circuits Syst. Comput., 2024)

Robust multimodal federated learning for non-IID multimodal data with incompleteness. - Songcan Yu; Kaiming Zhu; Feiyuan Liang; Junbo Wang 001; Krishna Kant 001; Ling Yin (Future Gener. Comput. Syst., 2026)