Everybody knows about Gaussian distribution, and Gaussian is very popular in Bayesian world and even in our life. This article summaries typical operation of Gaussian, and something about Truncated Guassian distribution. pdf(probability density funct…

原文:http://dongguo.me/blog/2014/01/01/expectation-propagation/ 简介 第一次接触EP是10年在百度实习时,当时组里面正有计划把线上的CTR预估模型改成支持增量更新的版本,读到了微软一篇基于baysian的CTR预估模型的文章(见推荐阅读5),文章中没有给出推导的细节,自己也没有继续研究.今年在PRML中读Approximal inference这章对EP有了一些了解,同时参考了其它相关的一些资料,在这里和大家探讨. 什么是期望传播 期望…

Introduction to Gaussian Processes Gaussian processes (GP) are a cornerstone of modern machine learning. They are often used for non-parametric regression and classification, and are extended from the theory behind Gaussian distributions and Gaussian…

Warming Up Before we talk about multivariate Gaussian, let's first review univariate Gaussian, which is usually called "Normal Distribution": \[ X \sim N(\mu,\ \sigma^2) = \frac{1}{\sqrt{2\pi}\sigma} e^{ -\frac{(x-\mu)^2}{2\sigma^2}} \] where \(…

import numpy as np import matplotlib.pyplot as plt import mpl_toolkits.axisartist as axisartist from mpl_toolkits.mplot3d import Axes3D #画三维图不可少 from matplotlib import cm #cm 是colormap的简写 #定义坐标轴函数 def setup_axes(fig, rect): ax = axisartist.Subplot(fi…

In recent years, Kernel methods have received major attention, particularly due to the increased popularity of the Support Vector Machines. Kernel functions can be used in many applications as they provide a simple bridge from linearity to non-linear…

转自 http://www.zhizhihu.com/html/y2010/2292.html Kernel Functions Below is a list of some kernel functions available from the existing literature. As was the case with previous articles, every LaTeX notation for the formulas below are readily availabl…

catalogue . 个人理解 . 基本使用 . MNIST(multiclass classification)入门 . 深入MNIST . 卷积神经网络:CIFAR- 数据集分类 . 单词的向量表示(Vector Representations of Words) . 循环神经网络(RNN).LSTM(Long-Short Term Memory, LSTM) . 用深度学习网络搭建一个聊天机器人 0. 个人理解 在学习的最开始,我在这里写一个个人对deep leanring和神经网络的粗…

2.1.2 下载CIFAR-10 数据 python cifar10_download.py # Copyright 2015 The TensorFlow Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. #…

==================================================================== This article came from here. Thanks for zhizhihu. ==================================================================== Kernel Functions Below is a list of some kernel functions avai…

安装TensorFlow  包依赖 C:\Users\sas> pip3 install --upgrade tensorflow Collecting tensorflow Downloading https://files.pythonhosted.org/packages/35/f6/8af765c7634bc72a902c50d6e7664cd1faac6128e7362510b0234d93c974/tensorflow-1.7.0-cp36-cp36m-win_amd64.whl (…

##Advice for Applying Machine Learning Applying machine learning in practice is not always straightforward. In this module, we share best practices for applying machine learning in practice, and discuss the best ways to evaluate performance of the le…

cifar10数据集 CIFAR-10 是由 Hinton 的学生 Alex Krizhevsky 和 Ilya Sutskever 整理的一个用于识别普适物体的小型数据集.一共包含 10 个类别的 RGB 彩色图片 :飞机( airplane ).汽车( automobile ).鸟类( bird ).猫( cat ).鹿( deer ). 狗( dog ).蛙类( frog ).马( horse ).船( ship )和卡车( truck ).图片的尺寸为 32 × 32 ,数据集中一共有…

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…

该类是生成一个验证码的类,集合了网上大部分的C#关于GDI+的文章进行多次改进,现在已经形成了可在生产环节中使用的验证码. 该验证码加入了背景噪点,背景噪点曲线和直线,背景噪点文字以及扭曲,调暗,模糊等.完全可以实现防识别. 对安全性要求比较高的网站尤其适用. 同时该类还还收集了GDI+的图像处理方面的函数,包括雾化,扭曲,水波,锐化,高斯模糊,画直线,画曲线生成随机颜色,缩放图片,柔化图片,图片黑白化,增加曝光度,RGB滤镜,绘制圆角等功能. using System; using Syste…

"利用给定像素周围的像素的值决定此像素的最终的输出值“ 教学效果: 策略: 1. 拉普拉斯,突出小细节: . 梯度,突出边缘: . 平滑过的梯度图像用于掩蔽: . 灰度变换,增加灰度动态范围. 扩展阅读: 使用模糊技术进行 灰度变换 和 空间滤波 . 线性空间滤波 Some neighborhood operations (邻域算子): (a) original image; (b) blurred; (c) sharpened; (d) smoothed with edge-preservin…

PRML Chapter 2. Probability Distributions P68 conjugate priors In Bayesian probability theory, if the posterior distributions p(θ|x) are in the same family as the prior probability distributionp(θ), the prior and posterior are then called conjugate d…

1． Matlab基础 1.1     数据格式 Matlab默认的数据格式为双精度浮点数的矩阵或数组,同时支持其它数据类型.Matlab将单变量看作1´1的数组.Matlab支持的数据类型如下: 索引值从1开始.字符串须用单引号括起来.有些matlab函数或操作符只能用于双精度浮点数. 1.2 基本运算 1.2.1 赋值,如 A = [1 2 3],A = [1,3,5],A = [1:3],A = [1:0.5:3],则A是个行向量,各元素值分别为:1 2 3    1 3 5      …

代码: #include <stdio.h> #include <opencv/highgui.h> #include <opencv/cv.h> #include <opencv_libs.h> /* *<学习OpenCV>第五章第二题 * 完成时间:21:43 10/13 星期日 2013 * 作者:qdsclove@163.com */ /* Image Size */ #define IMG_SIZE 100 /* * Window Ti…

点击查看Evernote原文. #@author: gr #@date: 2014-10-17 #@email: forgerui@gmail.com Fundamental 一. 矩阵的迹.秩 矩阵的秩: A的线性无关的极大数目,化简后他的非零项行数 矩阵的迹: 矩阵主对角线上的元素的和. # 矩阵的迹 trAB = trBA 二.非参数方法 非参数方法是数理统计学的一个分支,一般认为在一个统计推断问题中,如给定或者假定了总体分布的具体形式,只是其中含有若干个参数,要基于来自总体的样本对这些参…

The Model Complexity Myth (or, Yes You Can Fit Models With More Parameters Than Data Points) An oft-repeated rule of thumb in any sort of statistical model fitting is "you can't fit a model with more parameters than data points". This idea appea…

转自:http://blog.csdn.net/cyh_24/article/details/51537709 solver.prototxt net: "models/bvlc_alexnet/train_val.prototxt" test_iter: 1000 # test_interval: 1000 # base_lr: 0.01 # 开始的学习率 lr_policy: "step" # 学习率的drop是以gamma在每一次迭代中 gamma: 0.1…

很早之前写过<双边滤波算法的简易实现bilateralFilter>. 当时学习参考的代码来自cuda的样例. 相关代码可以参阅: https://github.com/johng12/cudaSamples/tree/master/cudaSamples/3_Imaging/bilateralFilter 由于算法逻辑非常清晰,就不多解释了. 需要补课的,请移步<o(1)复杂度之双边滤波算法的原理.流程.实现及效果.> 代码见:bilateralFilter_cpu.cpp 文件…

http://blog.csdn.net/pipisorry/article/details/53635895 核密度估计Kernel Density Estimation(KDE)概述 密度估计的问题 由给定样本集合求解随机变量的分布密度函数问题是概率统计学的基本问题之一.解决这一问题的方法包括参数估计和非参数估计. 参数估计 参数估计又可分为参数回归分析和参数判别分析.在参数回归分析中,人们假定数据分布符合某种特定的性态,如线性.可化线性或指数性态等,然后在目标函数族中寻找特定的解,即确定回…

Week Six F Score \[\begin{aligned} P &= &\dfrac{2}{\dfrac{1}{P}+\dfrac{1}{R}}\\ &= &2 \dfrac{PR}{P+R} \end{aligned}\] Week Seven Support Vector Machine Cost Function \[\begin{aligned} &\min_{\theta}\lbrack-\dfrac{1}{m}{\sum_{y_{i}\in Y…

$\bf 摘要$: 本文给出了王大凯等编的<图像处理中的偏微分方程方法>第 6.2 节的详细论述. $\bf 关键词$: 图像复原; TV 模型; matlab 编程 1. 前言 图像在形成.传输和存储过程中中, 图像质量可能退化 (degradation). 而退化的图像可用数学模型: $$\bee\label{1:d} u_0=h_d*f+n \eee$$来描述, 其中 (1)$f(x,y)$ 是理想的图像; (2)$h_d(x,y)$ 是成像系统的点弥散函数 (point-spread…

Using the latest advancements in AI to predict stock market movements 2019-01-13 21:31:18 This blog is copied from: https://github.com/borisbanushev/stockpredictionai In this notebook I will create a complete process for predicting stock price moveme…

这里罗列一些看完此书后遗留的问题: 常用 model 通过 BP/LBP 重新审视 inference 部分 Lauritzen algorithm/Lauritzen-Spiegelhalter algorithm turbo codec 与 LBP Gaussian processes 与 Gaussian MRF,上面的 EP BDe prior Dirichlet process Markov logic nets 上的 structure learning 与 training/inf…

1. Canny介绍 Canny算子与Marr(LoG)边缘检测方法类似,也属于是先平滑后求导数的方法.John Canny研究了最优边缘检测方法所需的特性,给出了评价边缘检测性能优劣的三个指标: 1  好的信噪比,即将非边缘点判定为边缘点的概率要低,将边缘点判为非边缘点的概率要低: 2  高的定位性能,即检测出的边缘点要尽可能在实际边缘的中心: 3  对单一边缘仅有唯一响应,即单个边缘产生多个响应的概率要低,并且虚假响应边缘应该得到最大抑制. 2. Canny检测实现过程 第一步:灰度化  第…

sustiva.pdb PDB: 1FKO Create parameter and coordinate files for Sustiva 1. 加氢: $ reduce sustiva.pdb > sustiva_h.pdb sed -i s/"EFZ"/"SUS"/g sustiva_h.pdb 加氢完毕后把文件内所有“EFZ”换为“SUS”. 2.转换为mol2格式: $ antechamber -i sustiva_new.pdb -fi pdb…