Theoretically, we prove that implicit MAML can compute accurate meta-gradients with a memory footprint no more than that which is required to compute a single inner loop gradient and at no overall increase in the total computational cost. Experimentally, we show that these benefits of implicit ...
Meta-learning with implicit gradients--nips19 论文思想 Few-shot case formula Implicit MAML Algorithm Practical Algorithm 论文思想 原始的MAML算法一个很大的挑战是外循环(元更新)需要通过对内循环(梯度自适应)过程进行求导,一般就要求存储和计算高阶导数。这篇论文的核心是利用隐微分方法,... 查看原文 李宏毅—...
使其学习率也可以随着loss的改变进行改变,进一步提升了训练效率;华盛顿大学的Aravind Rajeswaran发表的论文Meta-Learning with Implicit Gradients提出新的损失函数,用以解决MAML可能出现的梯度消失问题。
51、Alpha MAML: Adaptive Model-Agnostic Meta-Learning,2019 52、Meta-Learning with Implicit Gradients,2019 53、Efficient Meta Learning via Minibatch Proximal Updat,2019 54、Meta-Curvature,2019 55、Learning Unsupervised Learning Rules,2019 56、Meta Domain Adaptation:Meta-Learning For Few-Shot Learning Un...
Meta-learning with implicit gradients. In: Advances in Neural Information Processing Systems. 2019. p. 113–124. Champion M, Picheny V, Vignes M. Inferring large graphs using l (1)-penalized likelihood (vol 28, pg 905, 2018). Stat Comput. 2018;28(6):1231. Article Google Scholar ...
Gradient-based meta-learning with learned layerwise metric and subspace. ICML 2018 initialization-based [by DAPNA] How to train your MAML. ICLR 2019 MAML++ 就是一堆 trick Meta-Learning with Implicit Gradients. NeurIPS 2019 iMAML 大幅改動了 MAML 的架構 二作Chelsea Finn 大神 Reptile: A Scalabl...
Meta-learning with implicit gradients in a few-shot setting for medical image segmentation Widely used traditional supervised deep learning methods require a large number of training samples but often fail to generalize on unseen datasets. Theref... R Khadka,D Jha,S Hicks,... - 《Computers in...
Meta-Learning with Implicit Gradients [paper] Aravind Rajeswaran*, Chelsea Finn*, Sham Kakade, Sergey Levine --NeurIPS 2019 Model-Agnostic Meta-Learning using Runge-Kutta Methods [paper] Daniel Jiwoong Im, Yibo Jiang, Nakul Verma --arXiv ...
Meta-learning with implicit gradients--nips19 论文思想 Few-shot case formula Implicit MAML Algorithm Practical Algorithm 论文思想 原始的MAML算法一个很大的挑战是外循环(元更新)需要通过对内循环(梯度自适应)过程进行求导,一般就要求存储和计算高阶导数。这篇论文的核心是利用隐微分方法,... ...
requiring fewer examples and less trial-and-error. In short, welearn how to learnacross tasks. Likewise, when building machine learning models for a specific task, we often build on experience with related tasks, or use our (often implicit) understanding of the behavior of machine learning tech...