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擅长的技术
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发表了文章 2017-05-23
Sarsa(λ) and Q(λ) in Tabular Case
‘Thanks R. S. Sutton and A. G. Barto for their great work in Reinforcement Learning: An Introduction. Eligibility Traces in Prediction Problems In the backward view of TD(λ)TD(\lambda), t
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发表了文章 2017-05-19
Continuous Multi-Step TD, Eligibility Traces and TD(λ): A brief note
Thanks Richard S. Sutton and Andrew G. Barto for their great work in Reinforcement Learning: An Introduction. We focus on episodic case only and deal with continuous state and action space
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发表了文章 2017-05-15
Reinforcement Learning in Continuous State and Action Spaces: A Brief Note
Thanks Hado van Hasselt for the great work. Introduction In the problems of sequential decision making in continuous domains with delayed reward signals, the main purpose for the algori
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发表了文章 2017-05-06
Fisher判别分析简述
Supervised Dimension Reduction Greater dimensionality always brings about more difficult learning tasks. Here we introduce a supervised dimension reduction method based on linear dimension
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发表了文章 2017-05-05
浅析利用高斯核函数进行半监督分类
Laplacian Regularization In Least Square learning methods, we calculate the Euclidean distance between sample points to find a classifier plane. However, here we calculate the minimum dist
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发表了文章 2017-05-04
Texmaker 4.5 for Windows x64 安装配置方法
Texmaker 是一款易用性很强的免费Latex编辑工具，支持Win/Linux/OS X。下面介绍下Texmaker的安装配置方法： 首先，为你的系统配置Latex发行版环境，texmaker是不包含Latex环境的，这一点不如WinEdit。目前Win平台最好的latex发行版是Miktex，官网如下： Miktex官网地址 根据你的系统下载合适版本安装它，安装过后
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发表了文章 2017-05-02
Actor - Critic Algorithms: A Brief Note
Actor - Critic A class of algorithms that precede Q-Learning and SARSA are actor - critic methods. Refer to V. Konda and J. Tsitsiklis: Actor -critic algorithms. SIAM Journal on Contr
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发表了文章 2017-04-28
A Brief Note about Boltzmann/Softmax Exploration Strategy
One method that is often used in combination with the RL algorithms is the Beltzmann or softmax exploration strategy. The action selection strategy is still random, but selection probabili
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发表了文章 2017-04-24
工业机器人运动规划方法简述
工业机器人的运动 点到点运动：不需要在笛卡尔空间规划末端运动轨迹，机器人各个关节运动不需要联动。 轨迹跟踪运动：以点到点为基础，各个关节运动需要联动。 关节空间运动规划 目标：使关节空间轨迹平滑。 3次多项式插值 做如下假设：某个关节从t0t_{0} 时刻的位置q0q_{0} 运动到tft_{f} 时刻的位置qfq_{f} 。在t0t_{0} 和tft_{f}
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发表了文章 2017-04-18
一个简单谱聚类的例子
聚类是一种常见的无监督学习方法，目的在于从原始无标记数据中提取出分类标记。最简单的代表是K-means聚类，下面给出一个简单例子： n=300; c=3; t=randperm(n); x=[randn(1,n/3)-2 randn(1,n/3) randn(1,n/3)+2; randn(1,n/3) randn(1,n/3)+4 randn(1,n/3)]'
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发表了文章 2017-04-17
常用无监督降维方法简述
Unsupervised Dimension Reduction Data with high dimension is always difficult to tackle. One hand is that it requires tremendous computation resource. On the other hand, it is not so objec
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发表了文章 2017-04-14
局部异常因子与KL散度异常检测算法简述
Local Outlier Factor Given local outlier factors, we can detect the outliers that are always away from most of the samples. In order to outline the algorithm, some concepts must go first:
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发表了文章 2017-04-08
Logistic回归与最小二乘概率分类算法简述与示例
Logistic Regression & Least Square Probability Classification 1. Logistic Regression Likelihood function, as interpreted by wikipedia: https://en.wikipedia.org/wiki/Likelihood_f
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发表了文章 2017-04-07
集成剪枝分类算法的Adaboost集成学习算法示例
Adaboost (Adaptive Boosting) Classifier Boosting algorithms try to aggregate a couple of poor classifiers by order to make a powerful one. They assign weights to every labeled sample. When
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发表了文章 2017-04-07
集成剪枝分类算法的Bagging集成学习算法示例
Bagging (Bootstrap Aggregation) Pruning Classification is one of the simplest classification algorithms. It works just like if-then. However, when aggregating a lot of prunnings we are abl
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发表了文章 2017-04-05
ID3决策树与C4.5决策树分类算法简述
Let’s begin with ID3 decision tree: The ID3 algorithm tries to get the most information gain when grow the decision trees. The information gain is defined as Gain(A)=I(s1,s2,…,sm)−E(A) \
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发表了文章 2017-04-03
朴素贝叶斯分类算法简述
Naive Bayesian Algorithm Given some conditional probability, how to solve the conditional probability when we exchange positions of the two events? Or given P(A|B)P(A|B), how to solve P(B|
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发表了文章 2017-04-03
一个简单的Python plot曲线图示例
如下代码实现一个简单的曲线图绘制，采用Python 3.5.2 编写： import numpy as np import matplotlib.pyplot as plt x=np.linspace(-5,5,200) y=np.sin(x) yn=y+np.random.rand(1,len(y))*1.5 fig=plt.figure() ax=fig.add_s
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发表了文章 2017-04-02
机器学习中的常用距离
If x1,x2∈Rnx_{1}, x_{2}\in\mathbb{R}^{n}, then: 闵可夫斯基距离 Minkowski Distance d12=∑k=1n(x1k−x2k)p−−−−−−−−−−−−√p,p>0 d_{12}=\sqrt[\uproot{16}p]{\sum_{k=1}^{n}(x_{1k}-x_{2k})^{p}},\quad p>0欧
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发表了文章 2017-04-02
Python机器学习之NumPy库初探
import numpy as np from numpy import * #matrix an overview mylist=[1,2,3,4,5] a=10 mymatrix=np.mat(mylist) print(a*mymatrix) #special matrix myzero=np.zeros_like([3,5]) print(myzero) myze
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发表了文章 2017-04-01
Huber损失最小化学习法
Huber regression In least square learning methods, we make use of ℓ2\ell_{2} loss to make sure that we get a suitable outcome. However, in the robust point of view, it is always better to
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发表了文章 2017-03-31
l1约束的最小二乘学习
ℓ1\ell_{1}Constrained Least Squares In sparse learning, ℓ1\ell_{1} constrained LS, also known as Lasso Regression, is a common learning method: minθJLS(θ)s.t.∥θ∥1≤R \min_{\theta} J_{LS}(\
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发表了文章 2017-03-29
百行代码入门Python - Chapter 6
以下代码均采用Python 3.5.2编写。新建一个名为HelloWorld.py的文件，当然名字无所谓，输入以下代码： #filter def larger100(a): return a>100 for i in filter(larger100,[10,56,101,500]): print(i) #reduce from functoo
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发表了文章 2017-03-29
百行代码入门Python - Chapter 5
以下代码均采用Python 3.5.2 编写。新建一个名为HelloWorld.py的文件，当然名称无所谓，输入以下代码： #func return def line_conf(): b=15 def line(x): return 2*x+b b=5 return line my_line=line_conf() pr
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发表了文章 2017-03-28
百行代码入门Python - Chapter 4
以下代码均采用Python 3.5.2编写。新建一个名为HelloWorld.py的文件，当然名字无所谓，输入以下代码： #Class class Bird(object): feather= True reproduction="egg" def chirp(self, sound="some sound"): print(soun
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发表了文章 2017-03-27
百行代码入门Python - Chapter 3
以下代码采用Python3.5.2编写。 新建一个HelloWorld.py文件，当然文件名无所谓，只要不和下文中提及的文件重名即可，输入如下代码： #Class class Bird(object): feather= True reproduction="egg" def chirp(self, sound="some sound"):
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发表了文章 2017-03-26
百行代码入门Python - Chapter2
以下代码均采用Python 3.5.2编写。 建立一个名为HelloWorld.py的文件，当然名字无所谓，只要不是文字提及的其它文件名字即可，读懂以下代码方可轻松入门Python： #Class class Bird(object): feather= True reproduction="egg" def chirp(self, sound
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发表了文章 2017-03-26
百行代码入门Python - Chapter 1
以下代码均用Python 3.5.2编写。 一下代码建立在一个名为HelloWorld.py的主程序中，当然名字是次要的，随便取一个，只要不和本文中的其它文件重名即可。读懂以下示例代码即可入门Python： #Basics print("Hello World") example_dict={"liaobin":20, "yujing":18, "jiansheng":1
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发表了文章 2017-03-26
优化-拉格朗日乘子法简述
Lagrange Multipliers are used to solve the optimal value of multivariate functions under a group of constraints. By lagrange multipliers, we can convert an optimal problem with dd variables
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发表了文章 2017-03-26
高斯分布简述
A Brief of Gaussian Distribution Gaussian distribution, also known as normal distribution, is the most popular continuous probability distribution. In monovariate case, x∈(−∞,∞)x\in (-\i
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发表了文章 2017-03-25
l2约束的最小二乘学习法
ℓ2\ell_{2}constrained least squares In the simple least squares, noisy samples may lead to overfitting learning output. Therefore, it is rational to constrain the space of parameters. We
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发表了文章 2017-03-25
最小二乘学习算法基础
Least Squares Least squares regression is a traditional ML algorithm that minimizes the total square error between samples and learning output, i.e. minimize JLS(θ)=12∑i=1n(fθ(xi)−yi)2 J_
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发表了文章 2017-03-24
机器学习中的常见学习模型
Linear Model fθ(x)=∑j=1bθjϕj(x)=θTϕ(x) f_{\theta}(x)=\sum_{j=1}^{b}\theta_{j}\phi_{j}(x)=\theta^{T}\phi(x) where ϕ(x)\phi(x ) is the basis function vector and θ\theta is the parameter ve
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发表了文章 2017-03-12
Python如何搜索模块
在引入模块时，把库文件和应用文件放在同一文件夹下，当在该文件夹下运行程序时，Python会自动在当前文件夹下搜索它想要引入的模块。 但Python还会到其它地方寻找库： （1）标准库的安装路径； （2）操作系统环境变量PYTHONPATH所包含的路径。 标准库由Python官方提供，Python会自动搜索。如： import time 如果使用的是自定义模块，
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发表了文章
2017-05-23
Sarsa(λ) and Q(λ) in Tabular Case
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发表了文章
2017-05-19
Continuous Multi-Step TD, Eligibility Traces and TD(λ): A brief note
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发表了文章
2017-05-15
Reinforcement Learning in Continuous State and Action Spaces: A Brief Note
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发表了文章
2017-05-06
Fisher判别分析简述
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发表了文章
2017-05-05
浅析利用高斯核函数进行半监督分类
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发表了文章
2017-05-04
Texmaker 4.5 for Windows x64 安装配置方法
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发表了文章
2017-05-02
Actor - Critic Algorithms: A Brief Note
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发表了文章
2017-04-28
A Brief Note about Boltzmann/Softmax Exploration Strategy
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发表了文章
2017-04-24
工业机器人运动规划方法简述
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发表了文章
2017-04-18
一个简单谱聚类的例子
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发表了文章
2017-04-17
常用无监督降维方法简述
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发表了文章
2017-04-14
局部异常因子与KL散度异常检测算法简述
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发表了文章
2017-04-08
Logistic回归与最小二乘概率分类算法简述与示例
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发表了文章
2017-04-07
集成剪枝分类算法的Adaboost集成学习算法示例
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发表了文章
2017-04-07
集成剪枝分类算法的Bagging集成学习算法示例
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发表了文章
2017-04-05
ID3决策树与C4.5决策树分类算法简述
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发表了文章
2017-04-03
朴素贝叶斯分类算法简述
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发表了文章
2017-04-03
一个简单的Python plot曲线图示例
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发表了文章
2017-04-02
机器学习中的常用距离
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发表了文章
2017-04-02
Python机器学习之NumPy库初探
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