Learning to Propagate for Graph Meta-Learning

LU LIU, Tianyi Zhou, Guodong Long, Jing Jiang, Chengqi Zhang

Neural Information Processing Systems 

Inmost meta-learning methods, tasks areimplicitly related bysharing parameters oroptimizer. We develop a novel meta-learner of this type for prototype based classification, in which a prototype is generated for each class, such that the nearest neighbor search among the prototypes produces an accurate classification.

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