Efficient isometric multi-manifold learning based on the self-organizing method
Fan, Mingyu1; Zhang, Xiaoqin1; Qiao, Hong2,3; Zhang, Bo4,5
2016-06-01
发表期刊INFORMATION SCIENCES
卷号345页码:325-339
文章类型Article
摘要Geodesic distance, as an essential measurement for data similarity, has been successfully used in manifold learning. However, many geodesic based isometric manifold learning algorithms, such as the isometric feature mapping (Isomap) and GeoNLM, fail to work on data that distribute on clusters or multiple manifolds. This limits their applications because practical data sets generally distribute on multiple manifolds. In this paper, we propose a new isometric multi-manifold learning method called Multi-manifold Proximity Embedding (MPE) which can be efficiently optimized using the gradient descent method or the self-organizing method. Compared with the previous methods, the proposed method has two steps which can isometrically learn data distributed on several manifolds and is more accurate in preserving both the intra-manifold and the inter-manifold geodesic distances. The effectiveness of the proposed method in recovering the nonlinear data structure and clustering is demonstrated through experiments on both synthetically and real data sets. (C) 2016 Elsevier Inc. All rights reserved.
关键词Isomap Nonlinear Dimensionality Reduction Manifold Learning Pattern Analysis Multi-manifold Embedding
WOS标题词Science & Technology ; Technology
DOI10.1016/j.ins.2016.01.069
关键词[WOS]NONLINEAR DIMENSIONALITY REDUCTION ; CONNECTED NEIGHBORHOOD GRAPHS ; FEATURE-EXTRACTION ; FACE RECOGNITION ; ALGORITHM ; FRAMEWORK ; DISTANCE
收录类别SCI
语种英语
项目资助者NNSF of China Grant(61203241 ; NSF of Zhejiang Province(LY15F030011) ; Strategic Priority Research Program of the CAS(XDB02080003) ; NCMIS ; 61473212 ; 61472285 ; 6141101224 ; 61305035 ; 61379093 ; 11131006)
WOS研究方向Computer Science
WOS类目Computer Science, Information Systems
WOS记录号WOS:000372687300022
引用统计
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/11375
专题复杂系统管理与控制国家重点实验室_机器人理论与应用
作者单位1.Wenzhou Univ, Coll Math & Informat Sci, Wenzhou 325035, Peoples R China
2.Chinese Acad Sci, Inst Automat, State Key Lab Management Control Complex Syst, Beijing 100190, Peoples R China
3.CAS Ctr Excellence Brain Sci & Intelligence Techn, Shanghai 200031, Peoples R China
4.Chinese Acad Sci, LSEC, Beijing 100190, Peoples R China
5.Chinese Acad Sci, AMSS, Inst Appl Math, Beijing 100190, Peoples R China
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Fan, Mingyu,Zhang, Xiaoqin,Qiao, Hong,et al. Efficient isometric multi-manifold learning based on the self-organizing method[J]. INFORMATION SCIENCES,2016,345:325-339.
APA Fan, Mingyu,Zhang, Xiaoqin,Qiao, Hong,&Zhang, Bo.(2016).Efficient isometric multi-manifold learning based on the self-organizing method.INFORMATION SCIENCES,345,325-339.
MLA Fan, Mingyu,et al."Efficient isometric multi-manifold learning based on the self-organizing method".INFORMATION SCIENCES 345(2016):325-339.
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