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Jingdong book

机器学习理论及应用

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Books Computers & Internet Artificial Intelligence

Jingdong book

机器学习理论及应用

Name: 机器学习理论及应用
Brand: Jingdong book
SKU: 3118079481
Price: 53.75 USD
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Content Description

机器学习新方法研究是实现机器学服务各行各业的历史使命。根据这样的宗旨，《机器学习理论及应用》系统地介绍了李群机器学习、动态模糊机器学习、Agent普适机器学习和贝叶斯量子随机学习，共三篇十二章内容。
《机器学习理论及应用》可供计算机科学技术、认知科学、机器学习、人工智能、控制技术领域的高年级本科生和研究生作为教科书或参考书，也可供高校教师、科研院所的研究人员使用。

Catalogue

总序
前言
第1章引言
第1篇李群机器学习
第2章李群机器学习模型
2.1 引言
2.2 李群机器学习的概念
2.3 李群机器学习的代数模型
2.4 李群机器学习的几何模型
2.5 李群机器学习公理假设
2.6 李群机器学习Dynkin图的几何学习算法
2.7 李群机器学习的线形分类器设计
2.8 本章小结
参考文献

第3章李群机器学习(LML)子空间轨道生成算法
3.1 LML中偏序集及格的基本概念
3.2 LML子空间轨道生成格学习算法
3.3 LML中一般线性群GLn(Fn)作用下学习子空间轨道生成格学习算法
3 4 本章小结
参考文献

第4章李群机器学习的辛群学习算法
4.1 问题提出
4.2 李群机器学习中的辛群分类器设计
4.3 李群机器学与中的辛群分类器算法
4.4 应用实例
4.5 本章小结
参考文献

第5章李群机器学习的量子群学习算法
5.1 问题提出
5.2 李群机器学习中的最干群分类器构造方法
5.3 世子群学爿算法存分子对接巾的应用
5.4 本章小结
参考文献

第6章李群机器学习的纤堆丛学习算法
6.1 问题提出
6.2 纤维丛学习模型
6.3 纤维丛学习算法
6.4 本章小结
参考文献

第2篇动态模糊机器学习
第7章动态模糊机器掌习模型
7.1 问题提出
7.2 动态模糊机器学习模型
7.3 动态模糊机器学习系统的相关算法
7.4 动态模糊机器学习系统的过程控制模型
7.5 动态模糊关系学习算法
7.6 本章小结
参考文献

第8章动态模糊自主学习子空间学习算法
8.1 自主学习研究现状分析
8.2 基于DFL的自主学习子空间的理论体系
8.3 基于DFL的自主学习子空间学习算法
8.4 本章小结
参考文献

第9章动态模糊决策树学习
9.1 决策树学习的研究现状
9.2 动态模糊格的决策树方法
9.3 动态模糊决策树特殊属性处理技术
9.4 动态模糊决策树的剪枝策略
9.5 应用
9.6 本章小结
参考文献

第10章基于FDL的多Agent学习模型
10.1 引言
10.2 基于DFL的Agent心智模型
10.3 基于DFL的单Agent学习算法
10.4 基于DFL的多Agent学习模型
10.5 本章小结
参考文献

第3篇其他学习方法
第11章 Agent普适机器学习
11.1 引言
11.2 Agent普适机器学习
11.3 一种Agent普适机器学习分类器设计
11.4 本章小结
参考文献

第12章贝叶斯量子随机学习算法
12.1 问题提出
12.2 相关基本理论
12.3 贝叶斯量子随机学习模型
12.4 网络结构的贝叶斯量子随机学习算法设计
12.5 网络参数的贝叶斯量子随机学习算法设计
12.6 面向缺失数据的贝叶斯量子随机学习算法设计
12.7 本章小结
参考文献

附录
附录1 拓扑群
附录2 微分几何概念
附录3 流形学习算法
附录4 辛群的基本概念和性质
附录5 量子群的基本概念
附录6 纤维丛
附录7 动态模糊集(DFS)
附录8 动态模糊(DF)关系
附录9 动态模糊逻辑
附录10 动态模糊格及其性质
中英文名词对照

Book Abstract

科学通过理论、实践形成了人们解释自然界、人类社会等复杂系统的工具。在上世纪，整个科学逐步接受了一种新的科学研究方法，那就是机器学习。机器学习方法可以对研究由于受经济或者其他条件限制不能进行实验的数据进行有效分析。比如物质性质的分析、生命的演化等基本问题的回答都需要机器学习方法的支持。2001年美国航空航天局JPL实验室的科学家在《Science》上撰文指出：“机器学习对科学研究的整个过程正起到越来越大的作用，并预计该领域将取得稳定而快速的发展”；2003年美国国防部高级研究计划局DARPA开始启动了以机器学习为核心的PAL（Perception Assistant that Learns）计划，将机器学习技术的重要性上升到国家安全的高度来考虑；2004年，MIT Technology Review列出的“10 Emerging Technology That Wm Change Your World”将机器学习方面的研究列在第4位；2006年美国卡内基梅隆大学（CMU）专门成立了机器学习系；2008年，江泽民同志在上海交通大学学报上撰文《新时期我国信息技术产业的发展》指出：“……人工智能等前沿技术研究，推动信息学、物理学、生物学、认知学等学科的交叉融合，力争在多进制计算、语义分析、人脑结构模拟、机器学习等关键技术方面有新作为，实现原始性创新”。这充分说明机器学习方法在科学研究中扮演着重要的角色，许多重大科技活动越来越需要机器学习方法的参与。

Introduction

大学最重要的功能是向社会输送人才。大学对于一个国家、民族乃至世界的重要性和贡献度，很大程度上是通过毕业生在社会各领域所取得的成就来体现的。
中国科学技术大学建校只有短短的五十年，之所以迅速成为享有较高国际声誉的著名大学之一，主要就是因为她培养出了一大批德才兼备的优秀毕业生。他们志向高远、基础扎实、综合素质高、创新能力强，在国内外科技、经济、教育等领域做出了杰出的贡献，为中国科大赢得了“科技英才的摇篮”的美誉。
2008年9月，胡锦涛总书记为中国科大建校五十周年发来贺信，信中称赞说：半个世纪以来，中国科学技术大学依托中国科学院，按照全院办校、所系结合的方针，弘扬红专并进、理实交融的校风，努力推进教学和科研工作的改革创新，为党和国家培养了一大批科技人才，取得了一系列具有世界先进水平的原创性科技成果，为推动我国科教事业发展和社会主义现代化建设做出了重要贡献。
据统计，中国科大迄今已毕业的5万人中，已有42人当选中国科学院和中国工程院院士，是同期（自1963年以来）毕业生中当选院士数最多的高校之一。其中，本科毕业生中平均每1000人就产生1名院士和七百多名硕士、博士，比例位居全国高校之首。还有众多的中青年才俊成为我国科技、企业、教育等领域的领军人物和骨干。在历年评选的“中国青年五四奖章”获得者中，作为科技界、科技创新型企业界青年才俊代表，科大毕业生已连续多年榜上有名，获奖总人数位居全国高校前列。

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