Online Meta Learning 其中Meta-Update和Update-Procedure的过程如下图所示: Meta-Update和Update-Procedure 从算法1中可以看出该文章元学习思想是如何应用到在线学习中的。当某时刻t到来新的任务时,算法首先从该任务中采样数据点,接着执行元更新的步骤。在进行元更新时,训练使用的任务是从所有之前已经见到过的任务中采...
meta-learning把这个问题看作:训练一个模型,这个模型在新的任务会快速适应, 相反,online (regret based) learning把这个问题看作: 只训练一个模型,适应一系列的任务, 这篇文章将meta-learning和online learning结合, 提出follow the meta leader (FTML) 算法,即拓展了model agnostic meta-learning (MAML)算法, 在...
系统标签: meta learning online icml ftml mnist OnlineMeta-LearningChelseaFinnAravindRajeswaranShamKakadeSergeyLevinecentralcapabilityintelligentsystemscontinuouslybuilduponpreviousexpe-riencesspeedupenhancelearningnewtasks.Twodistinctresearchparadigmshavestud-iedquestion.Meta-learningviewsprob-lemaslearningpriorovermodelparame...
We propose the Online Meta-learning by\nParallel Algorithm Competition (OMPAC) method. In the OMPAC method, several\ninstances of a reinforcement learning algorithm are run in parallel with small\ndifferences in the initial values of the meta-parameters. After a fixed number\nof episodes, the ...
Furthermore, we observe that meta-learning can be used to meta-train a model such that this direct online adaptation with SGD is effective, which is otherwise not the case for large function approximators. In this work, we apply our meta-learning for online learning (MOLe) approach to model...
如果每一个replay-bufferBi仅包含任务专属的数据(分布较窄且任务之间分布无交叉),那么直接将meta-learning和offline learning的方法进行简单组合将会导致无法学到任务间的相关联的信息,从而使得meta-test情况下泛化失败。为了缓解该问题,本文通过混合不同任务的offline rollout创建了一个K-extended rollout。设有N个固定的...
called Meta Parameters Learning via Meta-Learning (MPML), to combine online hyper-parameter adjustment scheme into meta-learning algorithm, which reduces the need to tune hyper-parameters. Specifically, a basic learning rate for each training task is put forward. Besides, the proposed algorithm dyna...
In this paper, we propose an online meta-learning algorithm to enable VO networks to continuously adapt to new environments in a self-supervised manner. The proposed method utilizes convolutional long short-term memory (convLSTM) to aggregate rich spatial-temporal information in the past. The ...
本文是Online Hyper-parameter Learning for Auto-Augmentation Strategy的论文笔记,看见本文的读者欢迎评论区交流,加深彼此的理解。本文focus的任务是meta-learning的子任務,即希望机器可以自动制定data augme…
Meta learning 元学习算法(Meta Learning Algorithm, 简称MLA)与机器学习中的专家学习密切相关。上述三个类别(Follow the winner, Follow the loser, Pattern matching)侧重于单个策略,元学习侧重于结合多个策略,可以被配备现成算法的专家使用(即直接适用于FOF)。MLA假设有几个基础专家,要么来自同一个策略类,要么来自不...