Fang-Fei Qiao

A meta-learning and self-supervised framework for fast convergence in large-scale data optimization

A Meta-SelfSupervised Convergence Optimization Framework (MSCOF), which fuses self-supervised representation learning with meta-learning strategies to enhance adaptability and reduce convergence time under limited supervision, and maintains robustness across diverse data distributions and network conditions.