Towards Better Fairness-Utility Trade-off: A Comprehensive Measurement-Based Reinforcement Learning Framework. - Simiao Zhang; Jitao Bai; Menghong Guan; Yihao Huang 001; Yueling Zhang; Jun Sun 001; Geguang Pu (CoRR, 2023)

Reinforcement learning-driven deep question generation with rich semantics. - Menghong Guan; Subrota Kumar Mondal; Hong-Ning Dai; Haiyong Bao (Inf. Process. Manag., 2023)

CFP: A Reinforcement Learning Framework for Comprehensive Fairness-Performance Trade-Off in Machine Learning. - Simiao Zhang; Jitao Bai; Menghong Guan; Yueling Zhang; Jun Sun 001; Yihao Huang 001; Jiaping Wang; Chengcheng Wan 001; Ting Su 001; Geguang Pu (ICANN (1), 2024)

SAMFL: Secure Aggregation Mechanism for Federated Learning with Byzantine-robustness by functional encryption. - Menghong Guan; Haiyong Bao; Zhiqiang Li; Hao Pan; Cheng Huang 001; Hong-Ning Dai (J. Syst. Archit., 2024)

EBS-CFL: Efficient and Byzantine-robust Secure Clustered Federated Learning. - Zhiqiang Li; Haiyong Bao; Menghong Guan; Hao Pan; Cheng Huang 001; Hong-Ning Dai (AAAI, 2025)

PEFed: Enhancing privacy and efficiency in federated learning via removable perturbation and decentralized encryption. - Menghong Guan; Haiyong Bao; Jing Wang 239; Lu Xing; Hong-Ning Dai (Inf. Fusion, 2025)

UEFL: Universal and Efficient Privacy-Preserving Federated Learning. - Zhiqiang Li; Haiyong Bao; Hao Pan; Menghong Guan; Cheng Huang 001; Hong-Ning Dai (IEEE Internet Things J., 2025)

Mul_STK: Efficient and privacy-preserving query with spatio-temporal-keyword multiple attributes in cloud computing. - Lu Xing; Haiyong Bao; Menghong Guan; Jing Wang 239; Qinglei Kong; Hong-Ning Dai; Cheng Huang 001 (J. Syst. Archit., 2025)

DualGuard: Obfuscated Federated Learning With Two-Party Secure Robust Aggregation. - Hao Pan; Haiyong Bao; Menghong Guan; Zhiqiang Li; Cheng Huang 001; Hong-Ning Dai (IEEE Internet Things J., 2025)