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FirstChange
- 人工智能博弈树学习。用户是MAX方，电脑是MIN方，实现经典的分钱币游戏的与或图盲目搜索算法。-Artificial intelligence game tree learning. MAX user side, the computer is MIN parties to achieve the classic sub-games and coins or graph blind search algorithm.
SemiL
- 利用基于图的分类方法， 半监督学习 ，分类软件。-SemiL is efficient software for solving large scale semi-supervised learning or transductive inference problems using graph based approaches.
LGE
- 线性图嵌入方法，该方法是一种基于图框架的子空间学习方法，被用于LPP,NPE等流行学习方法中。-(Regularized) Linear Graph Embedding (Provides a general framework for graph based subspace learning. This function will be called by LPP, NPE, IsoProjection, LSDA, MMP ...)
networks1
- 随机网络学习笔记，中间有基本的随机图，规则图，以及其他图的生成代码-Random network learning notes, and there is a basic random figure, rules figure, and other graph generating code
networks2
- 随机网络学习笔记，中间有基本的随机图，规则图，以及其他图的生成代码-Random network learning notes, and there is a basic random figure, rules figure, and other graph generating code
networks3
- 随机网络学习笔记，中间有基本的随机图，规则图，以及其他图的生成代码-Random network learning notes, and there is a basic random figure, rules figure, and other graph generating code
networks4
- 随机网络学习笔记，中间有基本的随机图，规则图，以及其他图的生成代码-Random network learning notes, and there is a basic random figure, rules figure, and other graph generating code
metric-learning_survey_v2
- 关于metric learning的综述，涉及到许多的知识：SVM、kernel、SDP等-This paper surveys the field of distance metric learning from a principle perspective, and includes a broad selection of recent work. In particular, distance metric learning is reviewed under different
花书
- 深度学习是机器学习的一个分支，它能够使计算机通过层次概念来学习经验和理解世界。因为计算机能够从经验中获取知识，所以不需要人类来形式化地定义计算机需要的所有知识。层次概念允许计算机通过构造简单的概念来学习复杂的概念，而这些分层的图结构将具有很深的层次。本书会介绍深度学习领域的许多主题。(Deep learning is a branch of machine learning. It enables computers to learn experience and understand the