Corpus ID: 49653712

Large Margin Few-Shot Learning

@article{Wang2018LargeMF,
  title={Large Margin Few-Shot Learning},
  author={Yong Wang and Xiao-Ming Wu and Qimai Li and Jiatao Gu and Wangmeng Xiang and L. Zhang and Victor O. K. Li},
  journal={ArXiv},
  year={2018},
  volume={abs/1807.02872}
}
The key issue of few-shot learning is learning to generalize. This paper proposes a large margin principle to improve the generalization capacity of metric based methods for few-shot learning. To realize it, we develop a unified framework to learn a more discriminative metric space by augmenting the classification loss function with a large margin distance loss function for training. Extensive experiments on two state-of-the-art few-shot learning methods, graph neural networks and prototypical… Expand
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