27 citations · 40 across the 4 of their papers we have counts for
Showing cs.LGShow all
3 papers · 1 filter
cs.LG2020★ 2 cited
Model-Agnostic Learning to Meta-Learn
Arnout Devos, Yatin Dandi
In this paper, we propose a learning algorithm that enables a model to quickly exploit commonalities among related tasks from an unseen task distribution, before quickly adapting t…
cs.LG2020★ 27 cited
Self-Supervised Prototypical Transfer Learning for Few-Shot Classification
Carlos Medina, Arnout Devos, Matthias Grossglauser
Most approaches in few-shot learning rely on costly annotated data related to the goal task domain during (pre-)training. Recently, unsupervised meta-learning methods have exchange…
cs.LG2019★ 4 cited
Regression Networks for Meta-Learning Few-Shot Classification
Arnout Devos, Matthias Grossglauser
We propose regression networks for the problem of few-shot classification, where a classifier must generalize to new classes not seen in the training set, given only a small number…