2.1. Binary Variables 1. Bernoulli distribution, p(x = 1|µ) = µ 2.Binomial distribution + 3.beta distribution(Conjugate Prior of Bernoulli distribution) The parameters a and b are often called hyperparameters because they control the distribution of
Cognition math based on Factor Space Wang P Z1, Ouyang H2, Zhong Y X3, He H C4 1Intelligence Engineering and Math Institute, Liaoning Technical Univ. Fuxin, Liaoning, 123000, China 2Jie Macroelectronics co. Ltd, Shanghai, 200000, China 3 I & CE Colle
Nice R Code Punning code better since 2013 RSS Blog Archives Guides Modules About Markov Chain Monte Carlo 10 JUNE 2013 This topic doesn’t have much to do with nicer code, but there is probably some overlap in interest. However, some of the topics th
Chapter 1.6 : Information Theory Chapter 1.6 : Information Theory Christopher M. Bishop, PRML, Chapter 1 Introdcution 1. Information h(x) Given a random variable and we ask how much information is received when we observe a specific value for thi
A Statistical View of Deep Learning (IV): Recurrent Nets and Dynamical Systems Recurrent neural networks (RNNs) are now established as one of the key tools in the machine learning toolbox for handling large-scale sequence data. The ability to specify
Suppose a joint state representing a set of \(N_{n}\) nodes moving in a field\[ \textbf{X}= \begin{bmatrix} \left(\textbf{x}^{1}\right)^{T} & \left(\textbf{x}^{2}\right)^{T} & \cdots & \left(\textbf{x}^{N_{n}}\right)^{T} \\ \en
In statistics and in statistical physics, Gibbs sampling or a Gibbs sampler is aMarkov chain Monte Carlo (MCMC) algorithm for obtaining a sequence of observations which are approximated from a specifiedmultivariate probability distribution (i.e. from
Relevant Readable Links Name Interesting topic Comment Edwin Chen 非参贝叶斯 徐亦达老板 Dirichlet Process 学习目标:Dirichlet Process, HDP, HDP-HMM, IBP, CRM Alex Kendall Geometry and Uncertainty in Deep Learning for Computer Vision 语义分割 colah's blog Feature Visu
CVPR2015 Papers震撼来袭! CVPR 2015的文章可以下载了,如果链接无法下载,可以在Google上通过搜索paper名字下载(友情提示:可以使用filetype:pdf命令). Going Deeper With ConvolutionsChristian Szegedy, Wei Liu, Yangqing Jia, Pierre Sermanet, Scott Reed, Dragomir Anguelov, Dumitru Erhan, Vincent Vanhoucke
