题名 | Online data clustering using variational learning of a hierarchical dirichlet process mixture of dirichlet distributions |
作者 | |
发表日期 | 2014 |
会议名称 | 19th International Conference on Database Systems for Advanced Applications (DASFAA) |
会议录名称 | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
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ISSN | 0302-9743 |
卷号 | 8505 LNCS |
页码 | 18-32 |
会议日期 | APR 21-24, 2014 |
会议地点 | Bali, INDONESIA |
摘要 | This paper proposes an online clustering approach based on both hierarchical Dirichlet processes and Dirichlet distributions. The deployment of hierarchical Dirichlet processes allows to resolve difficulties related to model selection thanks to its nonparametric nature that arises in the face of unknown number of mixture components. The consideration of the Dirichlet distribution is justified by its high flexibility for non-Gaussian data modeling as shown in several previous works. The resulting statistical model is learned using variational Bayes and is evaluated via a challenging application namely images clustering. The obtained results show the merits of the proposed statistical framework. © 2014 Springer-Verlag Berlin Heidelberg. |
关键词 | Dirichlet distribution Hierarchical Dirichlet process Image clustering Mixture models Online learning Variational inference |
DOI | 10.1007/978-3-662-43984-5_2 |
URL | 查看来源 |
收录类别 | CPCI-S |
语种 | 英语English |
WOS研究方向 | Computer Science |
WOS类目 | Computer Science, Information Systems ; Computer Science, Theory & Methods |
WOS记录号 | WOS:000343882500002 |
Scopus入藏号 | 2-s2.0-84958527605 |
引用统计 | |
文献类型 | 会议论文 |
条目标识符 | https://repository.uic.edu.cn/handle/39GCC9TT/13289 |
专题 | 个人在本单位外知识产出 理工科技学院 |
通讯作者 | Bouguila, Nizar |
作者单位 | Concordia Institute for Information Systems Engineering,Concordia University,Montreal, QC,Canada |
推荐引用方式 GB/T 7714 | Fan, Wentao,Bouguila, Nizar. Online data clustering using variational learning of a hierarchical dirichlet process mixture of dirichlet distributions[C], 2014: 18-32. |
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