1.基本采样算法(Basic Sampling Algorithms) 1.1.标准概率分布(Standard distributions) 1.2.拒绝采样(Rejection sampling) 1.3.可调节的拒绝采样(Adaptive rejection sampling) 1.4.重要采样(Importance sampling) 1.5.采样-重要性-重采样(Sampling-importance-resampling) 1.6.采样与EM算法(Sampling and EM alg…

主讲人 网络上的尼采 (新浪微博: @Nietzsche_复杂网络机器学习) 网络上的尼采(813394698) 9:05:00  今天的主要内容:Markov Chain Monte Carlo,Metropolis-Hastings,Gibbs Sampling,Slice Sampling,Hybrid Monte Carlo. 上一章讲到的平均场是统计物理学中常用的一种思想,将无法处理的复杂多体问题分解成可以处理的单体问题来近似,变分推断便是在平均场的假设约束下求泛函L(Q)极值的最优化…

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…

从随机过程到马尔科夫链蒙特卡洛方法 1. Introduction 第一次接触到 Markov Chain Monte Carlo (MCMC) 是在 theano 的 deep learning tutorial 里面讲解到的 RBM 用到了 Gibbs sampling,当时因为要赶着做项目,虽然一头雾水,但是也没没有时间仔细看.趁目前比较清闲,把 machine learning 里面的 sampling methods 理一理,发现内容还真不少,有些知识本人也是一知半解,所以这篇博客不可…

HDMI热插拔检测原理 HDMI(19Pin)/DVI(16 pin)的功能是热插拔检测(HPD),这个信号将作为主机系统是否对HDMI/DVI是否发送TMDS信号的依据.HPD是从显示器输出送往计算机主机的一个检测信号.热插拔检测的作用是当显示器等数字显示器通过DVI接口与计算机主机相连或断开连接时,计算机主机能够通过HDMI/DVI的HPD引脚检测出这一事件,并做出响应. 在传输信号上来讲,HDMI与DVI完全兼容,只是接口封装不一样而已,下面以HDMI为例讲述HPD的原理和实现方式.下图为…

HDMI能够称霸为王者之尊吗?目前消费者陷入的困境就是Audio/Video的连接线数量过度庞大,而HDMI最大卖点之一就是可使用单一的连接线完全取代众多的影音连接线,简洁又方便.缺点是技术版本变动太快,2006年6月,1.3版本正式出笼.虽然HDMI是从DVI变身而来,但DVI却仅局限于视频(Video)的传送,HDMI则是跨及音频与视频,技术的层次较高也比较复杂. 如果认真追究起来,过去在视频领域里,其实还存在有一个称之为D端子的连接器,据不同的影像格式而区分为D1-D5.由于目前仅在日本当…

Using SMOTEBoost and RUSBoost to deal with class imbalance from:https://aitopics.org/doc/news:1B9F7A99/ Binary classification with strong class imbalance can be found in many real-world classification problems. From trying to predict events such as n…

  论文链接:Going deeper with convolutions 代码下载: Abstract We propose a deep convolutional neural network architecture codenamed Inception that achieves the (ILSVRC14). The main hallmark of this architecture is the improved utilization of the computing res…

Abstract - Undersampling is a popular method in dealing with class-imbalance problems, which uses only a subset of the majority class and thus is very efficient. The main deficiency is that many majority class examples are ignored. We propose two alg…

How to generate a sample from $p(x)$? Let's first see how Matlab samples from a $p(x)$. In Matlab, there are several common probability distributions. Try univariate Gaussian distribution p= normpdf(linspace(xmin , xmax , num_of_points) , mean, stand…