In this paper we propose MetAdapt that not only meta-searches for an optimized architecture for FSL using Network Architecture Search (NAS), but also results in ...

Dec 1, 2019 · In this work, we propose to employ tools inspired by the Differentiable Neural Architecture Search (D-NAS) literature in order to optimize the architecture for ...

Sep 1, 2021 · It is the backbone network architecture used to embed the images of the few-shot tasks. While first works on FSL resorted to small architectures ...

It is the backbone network architecture used to embed the images of the few-shot tasks. While first works on FSL resorted to small architectures with just a few ...

Semantic Scholar extracted view of "MetAdapt: Meta-Learned Task-Adaptive Architecture for Few-Shot Classification" by Sivan Doveh et al.

In this paper we propose MetAdapt that not only meta-searches for an optimized architecture for FSL using Network Architecture Search (NAS), but also results in ...

Mar 9, 2020 · Using the proposed approach we observe state-of-the-art results on two popu- lar few-shot benchmarks: miniImageNet and FC100. Keywords: Few-Shot ...

Dec 10, 2019 · These modules are added to the model and are meta-trained to predict the optimal network connections for a given novel task. Using the proposed ...

Few-shot learning aims to adapt knowledge learned from previous tasks to novel tasks with only a limited amount of labeled data.

MetAdapt: Meta-Learned Task-Adaptive Architecture for Few-Shot Classification · Sivan DovehEli Schwartz +4 authors. Leonid Karlinsky. Computer Science. Pattern ...