MetaFun: meta-learning with iterative functional updates
We develop a functional encoder-decoder approach to supervised meta-learning, where labeled data is encoded into an infinite-dimensional functional representation rather than a finite-dimensional one. Furthermore, rather than directly producing the representation, we learn a neural update rule resem...
Hlavní autoři: | , , , , |
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Médium: | Journal article |
Jazyk: | English |
Vydáno: |
MLResearch Press
2020
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