A Survey on Contrastive Self-supervised Learning

@article{Jaiswal2020ASO,
  title={A Survey on Contrastive Self-supervised Learning},
  author={Ashish Jaiswal and A. R. Babu and Mohammad Zaki Zadeh and D. Banerjee and F. Makedon},
  journal={ArXiv},
  year={2020},
  volume={abs/2011.00362}
}
  • Ashish Jaiswal, A. R. Babu, +2 authors F. Makedon
  • Published 2020
  • Computer Science
  • ArXiv
  • Self-supervised learning has gained popularity because of its ability to avoid the cost of annotating large-scale datasets. It is capable of adopting self-defined pseudo labels as supervision and use the learned representations for several downstream tasks. Specifically, contrastive learning has recently become a dominant component in self-supervised learning methods for computer vision, natural language processing (NLP), and other domains. It aims at embedding augmented versions of the same… CONTINUE READING
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