2 papers
cs.NE2026
Uncertainty-Aware Offline Data-Driven Multi-Objective Optimization
Huanbo Lyu, Miqing Li, Shiqiao Zhou +7
In offline data-driven multi-objective optimization (MOO), optimization is performed using surrogate models trained only on an offline dataset. These surrogate models contain inher…
cs.LG2024
FedGA: Federated Learning with Gradient Alignment for Error Asymmetry Mitigation
Chenguang Xiao, Zheming Zuo, Shuo Wang
Federated learning (FL) triggers intra-client and inter-client class imbalance, with the latter compared to the former leading to biased client updates and thus deteriorating the d…