中国机器学习白皮书

中国机器学习白皮书中国人工智能学会二○一五年十一月《中国人工智能系列白皮书》编委会主任：李德毅执行主任：王国胤副主任：杨放春谭铁牛黄河燕焦李成马少平刘宏蒋昌俊任福继杨强委员：陈杰董振江杜军平桂卫华韩力群何清黄心汉贾英民李斌刘民刘成林刘增良鲁华祥马华东马世龙苗夺谦朴松昊乔俊飞任友群孙富春孙长银王轩王飞跃王捍贫王万森王卫宁王小捷王亚杰王志良吴朝晖吴晓蓓夏桂华严新平杨春燕余凯余有成张学工赵春江周志华祝烈煌庄越挺《中国机器学习白皮书》编写组组长：陈松灿高阳组员：黄圣君李武军薛晖俞扬余志文詹德川詹志辉张利军张敏灵 庄福振

目录第1章引言 [229]等反馈受限问题中，主要目的是支持模糊决策，在探索和利用之间寻找最优的平衡。在解决这些实际问题时，又会发现一些新的问题，产生新的研究方向，促进在线学习算法和理论的发展。完全信息下的在线学习研究前沿包括非凸函数在线学习、非线性函数在线学习等问题。赌博机在线学习的研究热点主要围绕如何将算法和理论拓展到弱反馈场景，比如基于比较的赌博机。

第5章结束语本白皮书从主流机器学习技术、新兴机器学习技术以及大数据机器学习三方面对机器学习的研究和应用现状做了有选择的简要介绍。机器学习经过30余年的发展，目前已成为计算机科学中研究内涵极其丰富、新技术、新应用层出不穷的重要研究分支。国际上关于机器学习的主要学术会议包括每年定期举行的国际机器学习会议（ICML）、国际神经信息处理系统会议（NIPS）、欧洲机器学习会议（ECML）以及亚洲机器学习会议（ACML）等，主要学术期刊包括《MachineLearning》、《JournalofMachineLearningResearch》、《IEEETransactionsonNeuralNetworksandLearningSystems》等。此外，人工智能领域的一些主要国际会议（如IJCAI、AAAI等）和国际期刊（如《ArtificialIntelligence》、《IEEETransactionsonPatternAnalysisandMachineIntelligence》等）也经常发表与机器学习相关的最新研究成果。国内机器学习的重要学术活动包括每两年举行一次的中国机器学习会议（ChinaConferenceonMachineLearning,CCML），该会议目前由中国人工智能学会和中国计算机学会联合主办，中国人工智能学会机器学习专业委员会和中国计算机学会人工智能与模式识别专业委员会协办，目前已历经15届。此外，每年举行的中国机器学习及其应用研讨会（ChineseWorkshoponMachineLearningandApplications,MLA），该会议遵循“学术至上、其余从简”的原则，每届会议邀请海内外从事机器学习及相关领域研究的多位专家与会进行学术交流，包括特邀报告、顶会交流、以及TopConferenceReview等部分。迄今已历经13届，2015年度参会人数超过1200人。目前，大数据浪潮正对人类社会生活、科学研究的方方面面产生深刻影响。早期机器学习研究通常假设数据具有相对简单的特性，如数据来源单一、概念语义明确、数据规模适中、结构静态稳定等。当数据具有以上简单特性时，基于现有的机器学习理论与方法可以有效实现数据的智能化处理。然而，在大数据时代背景下，数据往往体现出多源异构、语义复杂、规模巨大、动态多变等特殊性质，为传统机器学习技术带来了新的挑战。为应对这一挑战，国内外科技企业巨头如谷歌、微软、亚马逊、华为、百度等纷纷成立以机器学习技术为核心的研究院，以充分挖掘大数据中蕴含的巨大商业与应用价值。可以预见，在未来相当长的一段时期内，机器学习领域的研究将以更广泛、更紧密的方式与工业界深度耦合，推动信息技术及产业的快速发展。

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