Maml and anil provably learn representations
… 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 …
with … Now we present new intuition for MAML and ANIL’s representation learning ability …
First-order ANIL provably learns representations despite overparametrisation
… 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 …
remains open for future work. Lastly, our work presents a provable shared representation learning …
Provable generalization of overparameterized meta-learning trained with sgd
… 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 …
approach, Model-Agnostic MetaLearning (MAML… ] studied MAML from a representation point …
MetaNO: How to transfer your knowledge on learning hidden physics
… Our approach is a provably universal solution operator for … a shared multi-task representation
that can generalize … popular meta-learning approaches such as MAML and ANIL, since the …
that can generalize … popular meta-learning approaches such as MAML and ANIL, since the …
First-order ANIL learns linear representations despite misspecified latent dimension
OK Yuksel, E Boursier, N Flammarion - arXiv preprint arXiv:2303.01335, 2023 - arxiv.org
… of ModelAgnostic Meta-Learning (MAML) algorithm on few-… In particular, FO-ANIL not
only learns the low-dimensional … We study FO-ANIL in a linear shared representation model …
only learns the low-dimensional … We study FO-ANIL in a linear shared representation model …
Adaptation: Blessing or Curse for Higher-way Meta-learning
… 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 …
… Maml and anil provably learn representations. In International Conference on Machine …
LaANIL: ANIL with Look-Ahead Meta-Optimization and Data Parallelism
V Tammisetti, K Bierzynski, G Stettinger… - Electronics, 2024 - mdpi.com
… 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…
advantages compared to MAML but faces challenges such as accuracy variance, slow initial learning…
Few-shot Multi-Task Learning of Linear Invariant Features with Meta Subspace Pursuit
C Zhang, L Liu, X Zhang - arXiv preprint arXiv:2409.02708, 2024 - arxiv.org
… -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 …
the shared representation, or the … As shown in our numerical experiments, ANIL requires more …
Global convergence of maml and theory-inspired neural architecture search for few-shot learning
… ) 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 …
and ANIL-kernel for the 5-cells and 8-… Provable guarantees for gradient-based meta-learning. In …
Sharp-maml: Sharpness-aware model-agnostic meta learning
… 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 …
Sharp-MAMLlow in ANIL can … MAML-ANIL is comparable in performance to SharpMAML …