… ANIL requires only constant error. We also show that ANIL learns the ground-truth representation
with … Now we present new intuition for MAML and ANIL’s representation learning ability …

… We study FO-ANIL in a linear shared representation model introduced in Sec… MAML,
remains open for future work. Lastly, our work presents a provable shared representation learning …

… learning is still limited. This paper studies the generalization of a widely used meta-learning
approach, Model-Agnostic MetaLearning (MAML… ] studied MAML from a representation point …

… not considerably modify the learned representations of a fully … ANIL offers numerous
advantages compared to MAML but faces challenges such as accuracy variance, slow initial learning…

… -SP), that provably learns this invariant subspace shared by … , are still capable of learning
the shared representation, or the … As shown in our numerical experiments, ANIL requires more …

… We first assess the quality of the feature extractors being learned by MAML, ANIL, ProtoNet,
… Maml and anil provably learn representations. In International Conference on Machine …

… ) under metalearning, and RN stands for the representation power … We use MAML-kernel
and ANIL-kernel for the 5-cells and 8-… Provable guarantees for gradient-based meta-learning. In …

… head with a frozen representation network from the meta-… 2020), we ask if incorporating
Sharp-MAMLlow in ANIL can … MAML-ANIL is comparable in performance to SharpMAML …

… for representation learning. Surprisingly, our analysis reveals that MAML and FedAvg are
indeed capable of learning … multi-task representation learning provably occurs for nonlinear …

… each few-shot learning task can be considered as a biased representation of the whole data.
… If we consider that the base learner is a neural network, eg, MAML or ANIL, which contains …