ee89223a2b625b5152132ed77abbcc79-Supplemental.pdf

The difference between the twodatasets comes from how CIFAR100 is split into meta-train / meta-validation / meta-test sets. Gradients have more noise due to less data variations, compared to higher resolution of miniImageNet images. The state-of-the-art method is shown to outperform ALFA+fo-Proto-MAML in Table D. Inthis section, we study howrobust the proposed meta-learner istochanges indomains, through additional experiments on cross-domain few-shot classification under similar settings to Section 4.3.2 During outer-loop optimization, 15 examples are sampled per each class forD0. All models were trained for 50000 iterations with the meta-batch size of 2 and 4 tasks for 5-shot and 1-shot, respectively.