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Title:
regularized local reconstruction for clustering
Author: Sun Jun ; Shen Zhiyong ; Su Bai ; Shen Yidong
Source: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Conference Name: 13th Pacific-Asia Conference on Knowledge and Data Mining
Conference Date: APR 27-30,
Issued Date: 2009
Conference Place: Bangkok, THAILAND
Keyword: Clustering ; Local Reconstruction ; Entropy Regularization
Publisher: ADVANCES IN KNOWLEDGE DISCOVERY AND DATA MINING, PROCEEDINGS
Publish Place: HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY
ISSN: 0302-9743
ISBN: 978-3-642-01306-5
Department: Sun, Jun; Shen, Zhiyong; Su, Bai; Shen, Yidong Chinese Acad Sci, Inst Software, State Key Lab Comp Sci, Beijing 100190, Peoples R China.
Sponsorship: Sirindhorn Int Inst Technol, Thammasat Univ, Chulalonkorn Univ, Asian Inst Technol, Natl Elect & Comp Technol Ctr, Thailand Convent & Exhibit Bureau, AF Off Sci Res, Asian Off Aerosp Res & Dev
English Abstract: Motivated by the local reconstruction approach to discovering low dimensional structure in high dimensional data; we propose a novel clustering algorithm that effectively utilizes local reconstruction information. We obtain the local reconstruction weights by minimizing the reconstruction error between each data point; and the reconstruction from its neighbors. An entropy regularization terns is incorporated into the reconstruction objective function so that the smoothness of the reconstruction weights call be explicitly controlled. The reconstruction weights are then used to obtain the clustering result by employing spectral clustering techniques. Experimental results on a number of datasets demonstrate that our algorithm performs well relative to other approaches, which validate the effectiveness of our approach for clustering.
Content Type: 会议论文
URI: http://ir.iscas.ac.cn/handle/311060/8360
Appears in Collections:计算机科学国家重点实验室 _会议论文

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Recommended Citation:
Sun Jun,Shen Zhiyong,Su Bai,et al. regularized local reconstruction for clustering[C]. 见:13th Pacific-Asia Conference on Knowledge and Data Mining. Bangkok, THAILAND. APR 27-30,.
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