Meta learning paper(一)：Learning to learn by gradient descent by gradient descent (Nips2016)

Meta learning paper(一)：Learning to learn by gradient descent by gradient descent (Nips2016)的相关文章

paper 124：【转载】无监督特征学习——Unsupervised feature learning and deep learning

来源:http://blog.csdn.net/abcjennifer/article/details/7804962 无监督学习近年来很热,先后应用于computer vision, audio classification和 NLP等问题,通过机器进行无监督学习feature得到的结果,其accuracy大多明显优于其他方法进行training.本文将主要针对Andrew的unsupervised learning,结合他的视频:unsupervised feature learning b

（转）Predictive learning vs. representation learning 预测学习 与 表示学习

Predictive learning vs. representation learning  预测学习 与 表示学习 When you take a machine learning class, there's a good chance it's divided into a unit on supervised learning and a unit on unsupervised learning. We certainly care about this distinction f

【转帖】UFLDL Tutorial（the main ideas of Unsupervised Feature Learning and Deep Learning）

UFLDL Tutorial From Ufldl Jump to: navigation, search Description: This tutorial will teach you the main ideas of Unsupervised Feature Learning and Deep Learning.  By working through it, you will also get to implement several feature learning/deep le

Deep Learning and Shallow Learning

Deep Learning and Shallow Learning 由于 Deep Learning 现在如火如荼的势头,在各种领域逐渐占据 state-of-the-art 的地位,上个学期在一门课的 project 中见识过了 deep learning 的效果,最近在做一个东西的时候模型上遇到一点瓶颈于是终于决定也来了解一下这个魔幻的领域. 据说 Deep Learning 的 break through 大概可以从 Hinton 在 2006 年提出的用于训练 Deep Belief

【转载】Discriminative Learning和Generative Learning

Discriminative Learning和Generative Learning 2011-12-08 10:47 1929人阅读 评论(2) 收藏 举报 variablesdependencies算法includeparametersexpress Discriminative 学习算法是一类模型化输入(X)输出(Y)的关系的方法,简单来说就好比中医,我们只知道用若干个药(当归,虎骨...)可以凑成一个药方,就能治疗跌打病痛.但我们并不去了解内部的原因,我们将其看做一个黑盒,只需了解X和

转：无监督特征学习——Unsupervised feature learning and deep learning

http://blog.csdn.net/abcjennifer/article/details/7804962 无监督学习近年来很热,先后应用于computer vision, audio classification和 NLP等问题,通过机器进行无监督学习feature得到的结果,其accuracy大多明显优于其他方法进行training.本文将主要针对Andrew的unsupervised learning,结合他的视频:unsupervised feature learning by A

【转载】 无监督特征学习——Unsupervised feature learning and deep learning

无监督特征学习——Unsupervised feature learning and deep learning 分类: Compression Computer Vision Machine Learning 杂感2012-07-31 15:48 36848人阅读 评论(61) 收藏 举报 目录(?)[+] 无监督学习近年来很热,先后应用于computer vision, audio classification和 NLP等问题,通过机器进行无监督学习feature得到的结果,其accurac

Machine Learning - Neural Networks Learning: Backpropagation in Practice

This series of articles are the study notes of " Machine Learning ", by Prof. Andrew Ng., Stanford University. This article is the notes of week 5, Neural Networks Learning. This article contains some topic about how to apply Backpropagation alg

Foundations of Machine Learning: The PAC Learning Framework(2)

Foundations of Machine Learning: The PAC Learning Framework(2) (一)假设集有限在一致性下的学习界. 在一篇文章中我们介绍了PAC-learnable的定义,以及证明了一个例子是PAC-learnable. 这一节我们介绍当hypothesis set是有限时,且算法$\mathcal{A}$相对与样本S满足一致性条件下的PAC问题.下一节介绍不一致条件下的PAC问题. 一致性(consistent):如果一个算法产生的假设$h_s$

Foundations of Machine Learning: The PAC Learning Framework(1)

写在最前:本系列主要是在阅读 Mehryar Mohri 等的最新书籍<Foundations of Machine Learning>以及 Schapire 和 Freund 的 <Boosting: Foundations and Algorithms>过程中所做的笔记.主要讨论三个部分的内容.第一部分是PAC的基本概念,介绍了泛化误差和经验误差,并且讨论了假设集$H$有限时的泛化边界.第二部分介绍了假设集$H$无限时的泛化边界,引入了三种衡量$H$复杂程度的机制,分别是Rad