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Conference Sep 2026

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.

Fang-Fei Qiao, Yu-Hui Liu, Jia Liu · 0 citations

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