Corpus ID: 236447721

CCGL: Contrastive Cascade Graph Learning

@article{Xu2021CCGLCC,
  title={CCGL: Contrastive Cascade Graph Learning},
  author={Xovee Xu and Fan Zhou and Kunpeng Zhang and Siyuan Liu},
  journal={ArXiv},
  year={2021},
  volume={abs/2107.12576}
}
  • Xovee Xu, Fan Zhou, +1 author Siyuan Liu
  • Published 2021
  • Computer Science
  • ArXiv
Supervised learning, while prevalent for information cascade modeling, often requires abundant labeled data in training, and the trained model is not easy to generalize across tasks and datasets. Semi-supervised learning facilitates unlabeled data for cascade understanding in pre-training. It often learns fine-grained feature-level representations, which can easily result in overfitting for downstream tasks. Recently, contrastive self-supervised learning is designed to alleviate these two… Expand

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