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cs.LG2025
PTCL: Pseudo-Label Temporal Curriculum Learning for Label-Limited Dynamic Graph
Shengtao Zhang, Haokai Zhang, Shiqi Lou +4
Dynamic node classification is critical for modeling evolving systems like financial transactions and academic collaborations. In such systems, dynamically capturing node informati…
cs.LG2024
Efficient and Scalable Deep Reinforcement Learning for Mean Field Control Games
Nianli Peng, Yilin Wang
Mean Field Control Games (MFCGs) provide a powerful theoretical framework for analyzing systems of infinitely many interacting agents, blending elements from Mean Field Games (MFGs…
cs.LG2024
Heterogeneous Graph Neural Networks with Loss-decrease-aware Curriculum Learning
Yili Wang
In recent years, heterogeneous graph neural networks (HGNNs) have achieved excellent performance in handling heterogeneous information networks (HINs). Curriculum learning is a mac…