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Valid accuracy (%) on novel classes of miniImageNet with only L_{MR} in FS-BAN. We show that, regularized by L_{MR}, the well-trained teacher network can be continually improved and gain better performance on unseen novel classes. It in turn leads to a better student with improved generalizability that even outperforms the teacher network consistently.
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