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HyperTransformer: Model Generation for Supervised and Semi-Supervised Few-Shot Learning. (arXiv:2201.04182v1 [cs.LG])
Jan. 13, 2022, 2:10 a.m. | Andrey Zhmoginov, Mark Sandler, Max Vladymyrov
cs.LG updates on arXiv.org arxiv.org
In this work we propose a HyperTransformer, a transformer-based model for
few-shot learning that generates weights of a convolutional neural network
(CNN) directly from support samples. Since the dependence of a small generated
CNN model on a specific task is encoded by a high-capacity transformer model,
we effectively decouple the complexity of the large task space from the
complexity of individual tasks. Our method is particularly effective for small
target CNN architectures where learning a fixed universal task-independent
embedding is …
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