The Rise of Meta Learning 2019-10-18 06:48:37 This blog is from: https://towardsdatascience.com/the-rise-of-meta-learning-9c61ffac8564 Connor Shorten Follow Oct 16 · 9 min read   https://openai.com/blog/solving-rubiks-cube/ Meta-Learning describes th…

原文链接:Meta Learning单排小教学 虽然Meta Learning现在已经非常火了,但是还有很多小伙伴对于Meta Learning不是特别理解.考虑到我的这个AI游乐场将充斥着Meta Learning的分析解读及各种原创思考,所以今天Flood就和大家做一个Meta Learning小教学,希望能够用最简短,最通俗的语言来让大家明白Meta Learning的概念,Meta Learning的几种研究方法,以及Meta Learning未来的发展,带大家上分!相信这个Meta L…

Visual Question Answering as a Meta Learning Task ECCV 2018 2018-09-13 19:58:08 Paper: http://openaccess.thecvf.com/content_ECCV_2018/papers/Damien_Teney_Visual_Question_Answering_ECCV_2018_paper.pdf 1. Introduction: 本文提出一种新的 VQA 思路,将 meta-learning 结…

深度学习课程笔记(十七)Meta-learning (Model Agnostic Meta Learning) 2018-08-09 12:21:33 The video tutorial can be found from: Model Agnostic Meta Learning Related Videos: My talk for Model Agnostic Meta Learning with domain adaptation Paper: https://arxiv.org/p…

Meta Learning/ Learning to Learn/ One Shot Learning/ Lifelong Learning 2018-08-03 19:16:56 本文转自:https://github.com/floodsung/Meta-Learning-Papers 1 Legacy Papers [1] Nicolas Schweighofer and Kenji Doya. Meta-learning in reinforcement learning. Neural…

Deep Meta Learning for Real-Time Visual Tracking based on Target-Specific Feature Space  2018-01-04  15:58:15  写在前面:为什么要看这个paper?这篇 paper 貌似是第一个将 meta-learning 应用到 visual tracking 领域的,取得了速度和精度较好的平衡. Introduction: 我们知道,tracking 中比较重要的就是 target object…

MetaPruning: Meta Learning for Automatic Neural Network Channel Pruning 2019-08-11 19:48:17 Paper: https://arxiv.org/pdf/1903.10258.pdf Code: https://github.com/liuzechun/MetaPruning 1. Background and Motivation:…

MetaPruning 2019-ICCV-MetaPruning Meta Learning for Automatic Neural Network Channel Pruning Zechun Liu (HKUST).Xiangyu Zhang (MEGVII).Jian Sun(MEGVII) GitHub:251 stars Citation:20 Motivation A typical pruning approach contains three stages: training…

目录 元学习(Meta-learning) 元学习被用在了哪些地方? Few-Shot Learning(小样本学习) 最近的元学习方法如何工作 Model-Agnostic Meta-Learning (MAML) 元学习(Meta-learning) 智能的一个关键方面是多功能性--做许多不同事情的能力.当前的AI系统可以做到精通于某一项技能,但是,如果我们要求AI系统执行各种看似简单的问题(用同一个模型去解决不同问题),它将会变得十分困难.相反,人类可以明智地利用以往经验并采取行动以适应各…

Learning to Learn Chelsea Finn    Jul 18, 2017 A key aspect of intelligence is versatility – the capability of doing many different things. Current AI systems excel at mastering a single skill, such as Go, Jeopardy, or even helicopter aerobatics. But…