<?xml version="1.0" encoding="utf-8" ?><rss version="2.0"><channel><title><![CDATA[treasuresss的专栏]]></title><description><![CDATA[]]></description><link>https://blog.youkuaiyun.com/treasuresss</link><language>zh-cn</language><generator>https://blog.youkuaiyun.com/</generator><copyright><![CDATA[Copyright &copy; treasuresss]]></copyright><item><title><![CDATA[ubuntu下的hadoop安装]]></title><link>https://blog.youkuaiyun.com/treasuresss/article/details/51365194</link><guid>https://blog.youkuaiyun.com/treasuresss/article/details/51365194</guid><author>treasuresss</author><pubDate>Tue, 10 May 2016 17:45:25 +0800</pubDate><description><![CDATA[1. 环境ubuntu 14.04 64位 
java 1.8.0_45（1.7即可） 
ssh（sshd运行）2. 安装版本hadoop2.7.2（http://hadoop.apache.org/releases.html）3. 安装过程1.下载hadoop2.7.2的binary版本 http://www.apache.org/dyn/closer.cgi/hadoop/common/hado]]></description><category></category></item><item><title><![CDATA[python脚本打包发布：pyinstaller]]></title><link>https://blog.youkuaiyun.com/treasuresss/article/details/51324677</link><guid>https://blog.youkuaiyun.com/treasuresss/article/details/51324677</guid><author>treasuresss</author><pubDate>Thu, 05 May 2016 17:21:00 +0800</pubDate><description><![CDATA[1 安装环境windows发行版：win7 64位 
python发行版：Anaconda2 pyinstaller安装pip install pyinstaller测试是否成功安装pyinstaller --version3.23 pyinstaller简例pyinstaller helloWorld.pyorpyinstaller --onefile helloWorld.py命令执行会生成两个]]></description><category></category></item><item><title><![CDATA[数值最优化]]></title><link>https://blog.youkuaiyun.com/treasuresss/article/details/50897408</link><guid>https://blog.youkuaiyun.com/treasuresss/article/details/50897408</guid><author>treasuresss</author><pubDate>Tue, 15 Mar 2016 17:48:13 +0800</pubDate><description><![CDATA[0. 数学基础多元函数 
1. 设多元函数 f:Rn→R f:R^n\rightarrow R  二次连续可微，则 f f  在 xx 处的梯度和Hessian矩阵为：∇f(x)=(∂f(x)∂x1,∂f(x)∂x2,⋯,∂f(x)∂xn)T \nabla f(x) = (\frac{\partial f(x)}{\partial x_1},\frac{\partial f(x)}{\partial]]></description><category></category></item><item><title><![CDATA[word2vec]]></title><link>https://blog.youkuaiyun.com/treasuresss/article/details/50813121</link><guid>https://blog.youkuaiyun.com/treasuresss/article/details/50813121</guid><author>treasuresss</author><pubDate>Sun, 06 Mar 2016 14:39:24 +0800</pubDate><description><![CDATA[Corpuszh_cn搜狗语料库：ftp://ftp.labs.sogou.com/Data/SogouCS/SogouCS.tar.gz 
中文维基百科语料库：https://dumps.wikimedia.org/zhwiki/latest/zhwiki-latest-pages-articles.xml.bz2en英文维基百科语料库：https://dumps.wikimedia.org/en]]></description><category></category></item><item><title><![CDATA[BP神经网络的反向求导]]></title><link>https://blog.youkuaiyun.com/treasuresss/article/details/50809148</link><guid>https://blog.youkuaiyun.com/treasuresss/article/details/50809148</guid><author>treasuresss</author><pubDate>Sat, 05 Mar 2016 16:39:17 +0800</pubDate><description><![CDATA[BP神经网络本文章主要是记录BP神经网络的反向求导的具体过程，主要参考是UFLDL Tutoial。 
中文版教程请戳此神经网络经典的神经网络是由多个感知器（神经元）构成的全连接的网络，本质上来说，这样的连接只是简单的线性加权和而已，所以每个神经元加上同一个非线性函数（如sigmoid，tanh等），使得网络能拟合非线性，其中这个非线性函数成为激活函数。符号描述为简便叙述，本文中的神经网络都是最简单]]></description><category></category></item><item><title><![CDATA[CNN]]></title><link>https://blog.youkuaiyun.com/treasuresss/article/details/50802426</link><guid>https://blog.youkuaiyun.com/treasuresss/article/details/50802426</guid><author>treasuresss</author><pubDate>Fri, 04 Mar 2016 14:37:39 +0800</pubDate><description><![CDATA[参考文献：GradientBased Learning Applied to Document Recognition - Yann LeCun Leon Bottou Yoshua Bengio and Patrick Haner Abst：杨乐村98年基于MNIST的LeNet-5的详细论文 
Unsupervised Feature Learning and Deep Learning：UF]]></description><category></category></item><item><title><![CDATA[My List of Perfect Software and Website]]></title><link>https://blog.youkuaiyun.com/treasuresss/article/details/50759492</link><guid>https://blog.youkuaiyun.com/treasuresss/article/details/50759492</guid><author>treasuresss</author><pubDate>Sun, 28 Feb 2016 12:05:09 +0800</pubDate><description><![CDATA[Green Software
SumatraPDF-3.1.1（Portable） : 小巧简洁的pdf阅读器
灵格斯词霸-2.9.2 (简体中文绿色便携版) : 屏幕取词划词功能极好，支持Sumatra PDF划词。
chrome extensions
Octotree：Github查看代码神器
Proxy SwitchyOmega：代理管理插件
划词翻译：如名
website
Smallpdf：]]></description><category></category></item><item><title><![CDATA[python matplotlib中文显示乱码解决]]></title><link>https://blog.youkuaiyun.com/treasuresss/article/details/50750325</link><guid>https://blog.youkuaiyun.com/treasuresss/article/details/50750325</guid><author>treasuresss</author><pubDate>Fri, 26 Feb 2016 15:48:30 +0800</pubDate><description><![CDATA[问题描述：python matplotlib绘图中文显示乱码 
问题根源：matplotlib的默认字体并非中文字体 
解决：设置为中文字体linux下查找中文字体：fc-list :lang=zh-cn #注意:前有个空格 
windows下中文字体路径：c:\windows\fonts\simsun.ttcfrom matplotlib.font_manager import FontPrope]]></description><category></category></item><item><title><![CDATA[Python Note]]></title><link>https://blog.youkuaiyun.com/treasuresss/article/details/50509415</link><guid>https://blog.youkuaiyun.com/treasuresss/article/details/50509415</guid><author>treasuresss</author><pubDate>Fri, 26 Feb 2016 09:31:47 +0800</pubDate><description><![CDATA[Python NotePython 中文官方文档str
str.translate(table [,deletechars]) -> string
>>> from string import punctuation
>>> s = 'abc,./123'
>>> s.translate(None , punctuation)
'abc123'
>>> s.translate('a'*256 , p]]></description><category></category></item><item><title><![CDATA[matplotlib Note]]></title><link>https://blog.youkuaiyun.com/treasuresss/article/details/50731248</link><guid>https://blog.youkuaiyun.com/treasuresss/article/details/50731248</guid><author>treasuresss</author><pubDate>Wed, 24 Feb 2016 16:00:00 +0800</pubDate><description><![CDATA[pyplot首先，先导入numpy和pyplotimport numpy as np
import matplotlib.pyplot as plt
简单画图示例：
x = np.linspace(-10,10,1000)
y = np.sin(x)
plt.plot(x,y,alpha=0.3)#alpha：float (0.0 transparent through 1.0 opaque)
pl]]></description><category></category></item><item><title><![CDATA[文章标题]]></title><link>https://blog.youkuaiyun.com/treasuresss/article/details/50730655</link><guid>https://blog.youkuaiyun.com/treasuresss/article/details/50730655</guid><author>treasuresss</author><pubDate>Wed, 24 Feb 2016 14:31:14 +0800</pubDate><description><![CDATA[date~$ date +%Y-%m-%d+%H:%M:%S
2016-01-28+09:39:55
~$ date +%Y-%m-%d --date="-1 day"
2016-01-27Custom Command
在~/.bashrc中添加alias命令，如：alias ll=”ls -al”
source ~/.bashrc使之立即生效
Simple Tutorial该section节选于C]]></description><category></category></item><item><title><![CDATA[ubuntu的virtualbox]]></title><link>https://blog.youkuaiyun.com/treasuresss/article/details/50563396</link><guid>https://blog.youkuaiyun.com/treasuresss/article/details/50563396</guid><author>treasuresss</author><pubDate>Fri, 22 Jan 2016 18:07:30 +0800</pubDate><description><![CDATA[系统版本：ubuntu 14.04问题：把大文件从共享文件夹中拷到虚拟机中的win7时，虚拟机崩溃了！解决：卸载重装，必须完全卸载！ 
sudo dpkg -P virtualbox-5.0 
官网下载deb重装]]></description><category></category></item><item><title><![CDATA[CNN Note]]></title><link>https://blog.youkuaiyun.com/treasuresss/article/details/50547224</link><guid>https://blog.youkuaiyun.com/treasuresss/article/details/50547224</guid><author>treasuresss</author><pubDate>Thu, 21 Jan 2016 11:45:07 +0800</pubDate><description><![CDATA[CNN Note本文主要记录些CNN相关的文章，以为备忘： 
1. Deep Learning（深度学习）学习笔记整理系列之（七） 
2. Deep Learning论文笔记之（四）CNN卷积神经网络推导和实现 
3. Deep Learning论文笔记之（五）CNN卷积神经网络代码理解 
4. 注解： 
1. 此文章详细介绍了卷积神经网络的历史和原理，入门必备。 
2.]]></description><category></category></item><item><title><![CDATA[LaTeX Note]]></title><link>https://blog.youkuaiyun.com/treasuresss/article/details/50546490</link><guid>https://blog.youkuaiyun.com/treasuresss/article/details/50546490</guid><author>treasuresss</author><pubDate>Wed, 20 Jan 2016 11:08:54 +0800</pubDate><description><![CDATA[LaTeX Note本Note仅对用过的语法、宏包等做备忘，以及一些总结：
基础知识
排版相关
数学相关
图片相关
其他
基础知识{}：必选参数 
[]：可选参数 
$ $：行内公式 
$$  $$：单行公式 
空白符基本没什么卵用 
    \\：换行排版相关“` tex 
\documentclass{article}\title{firstTest} 
\author{treasuresss]]></description><category></category></item><item><title><![CDATA[平方和的几何解释]]></title><link>https://blog.youkuaiyun.com/treasuresss/article/details/48371693</link><guid>https://blog.youkuaiyun.com/treasuresss/article/details/48371693</guid><author>treasuresss</author><pubDate>Thu, 24 Sep 2015 16:57:24 +0800</pubDate><description><![CDATA[平方和的几何解释高斯小时候被老师问到1+2+⋯+99+1001+2+\cdots +99+100的和，聪明机智的高斯几乎脱口而出5050。在我们现在看来其实很简单，也就是一个等差数列的求和公式而已： 
∑i=1ni=n(n+1)2\sum_{i=1}^ni = \frac {n (n+1)} 2 一般地，如果等差数列{aia_i}的公差为d，则：∑i=1nai=n(n+1)d2\sum_{i=1}^]]></description><category></category></item><item><title><![CDATA[《PCA的数学原理》读书笔记]]></title><link>https://blog.youkuaiyun.com/treasuresss/article/details/48195211</link><guid>https://blog.youkuaiyun.com/treasuresss/article/details/48195211</guid><author>treasuresss</author><pubDate>Fri, 11 Sep 2015 13:21:56 +0800</pubDate><description><![CDATA[《PCA的数学原理》读书笔记最近读了张洋的《 PCA的数学原理 》的文章，受益匪浅，但是文章中也有一些地方不甚明了，本着刨根问底的态度，在此写下自己的理解和阅读之中所遇到的困惑及明悟。作为一只数学狗，个人还是比较喜欢规范化的文字。首先定义一些符号：假设我们有mm个样本数据，每个样本都是一个nn维向量，那么我们的样本矩阵就是一个n×mn \times m的矩阵An∗mA_{n*m}，即以列为样本，行为]]></description><category></category></item><item><title><![CDATA[【HDU 1874 2544 2066 2112】 Dijkstra单源最短路径专题 —— 优先队列+邻接表/邻接矩阵]]></title><link>https://blog.youkuaiyun.com/treasuresss/article/details/45439813</link><guid>https://blog.youkuaiyun.com/treasuresss/article/details/45439813</guid><author>treasuresss</author><pubDate>Sat, 02 May 2015 14:36:22 +0800</pubDate><description><![CDATA[分别基于邻接表和邻接矩阵，采用优先队列高效实现Dijkstra最短路径算法。
Dijkstra练习题库]]></description><category></category></item><item><title><![CDATA[【SGU 180】Inversions —— 归并排序或树形数组计算逆序对]]></title><link>https://blog.youkuaiyun.com/treasuresss/article/details/45347923</link><guid>https://blog.youkuaiyun.com/treasuresss/article/details/45347923</guid><author>treasuresss</author><pubDate>Tue, 28 Apr 2015 23:36:43 +0800</pubDate><description><![CDATA[分别采用归并排序、树形数组来计算逆序对]]></description><category></category></item><item><title><![CDATA[【HDU 1754】I Hate It —— 线段树（数组和指针实现）]]></title><link>https://blog.youkuaiyun.com/treasuresss/article/details/45340279</link><guid>https://blog.youkuaiyun.com/treasuresss/article/details/45340279</guid><author>treasuresss</author><pubDate>Tue, 28 Apr 2015 18:28:52 +0800</pubDate><description><![CDATA[线段树（Segment Tree）的数组和指针实现]]></description><category></category></item><item><title><![CDATA[【HDU 1005】Number Sequence —— 找周期]]></title><link>https://blog.youkuaiyun.com/treasuresss/article/details/45313297</link><guid>https://blog.youkuaiyun.com/treasuresss/article/details/45313297</guid><author>treasuresss</author><pubDate>Mon, 27 Apr 2015 17:32:08 +0800</pubDate><description><![CDATA[原题链接




Number Sequence
Time Limit: 2000/1000 MS (Java/Others)    Memory Limit: 65536/32768 K (Java/Others)
Total Submission(s): 122213    Accepted Submission(s): 29653



Problem Descript]]></description><category></category></item></channel></rss>