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Parameter Identifiability in Statistical Machine Learning: A Review

文献类型：期刊论文

作者Ran, Zhi-Yong1; Hu, Bao-Gang2
刊名NEURAL COMPUTATION
出版日期2017-05-01
卷号29期号:5页码:1151-1203
关键词Parameter Identifiability Statistical Machine Learning
DOI10.1162/NECO_a_00947
文献子类Review
英文摘要This review examines the relevance of parameter identifiability for statistical models used in machine learning. In addition to defining main concepts, we address several issues of identifiability closely related to machine learning, showing the advantages and disadvantages of state-of- the-art research and demonstrating recent progress. First, we review criteria for determining the parameter structure of models from the literature. This has three related issues: parameter identifiability, parameter redundancy, and reparameterization. Second, we review the deep influence of identifiability on various aspects of machine learning from theoretical and application viewpoints. In addition to illustrating the utility and influence of identifiability, we emphasize the interplay among identifiability theory, machine learning, mathematical statistics, information theory, optimization theory, information geometry, Riemann geometry, symbolic computation, Bayesian inference, algebraic geometry, and others. Finally, we present a new perspective together with the associated challenges.
WOS关键词NATURAL GRADIENT DESCENT ; MULTILAYER NEURAL-NETWORKS ; SOFT COMMITTEE MACHINES ; INFORMATION CRITERION ; STRUCTURAL IDENTIFIABILITY ; COMPARTMENTAL-MODELS ; COMPUTER ALGEBRA ; LIKELIHOOD RATIO ; HIDDEN UNITS ; SINGULARITIES
WOS研究方向Computer Science ; Neurosciences & Neurology
语种英语
WOS记录号WOS:000399679500001
资助机构NSFC(61273196 ; 61620106003)
源URL[http://ir.ia.ac.cn/handle/173211/15089]  
专题自动化研究所_模式识别国家重点实验室_多媒体计算与图形学团队
作者单位1.Chongqing Univ Posts & Telecommun, Chongqing Key Lab Computat Intelligence, Sch Comp Sci & Technol, Chongqing 400065, Peoples R China
2.Chinese Acad Sci, Inst Automat, NLPR & LIAMA, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714		 Ran, Zhi-Yong,Hu, Bao-Gang. Parameter Identifiability in Statistical Machine Learning: A Review[J]. NEURAL COMPUTATION,2017,29(5):1151-1203.
APA Ran, Zhi-Yong,&Hu, Bao-Gang.(2017).Parameter Identifiability in Statistical Machine Learning: A Review.NEURAL COMPUTATION,29(5),1151-1203.
MLA Ran, Zhi-Yong,et al."Parameter Identifiability in Statistical Machine Learning: A Review".NEURAL COMPUTATION 29.5(2017):1151-1203.

入库方式： OAI收割

来源：自动化研究所

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