题名 | An online approach for learning non-Gaussian mixture models with localized feature selection |
作者 | |
发表日期 | 2013 |
会议名称 | 1st International Conference on Communications, Signal Processing, and their Applications (ICCSPA) |
会议录名称 | 2013 1st International Conference on Communications, Signal Processing and Their Applications, ICCSPA 2013
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会议日期 | FEB 12-14, 2013 |
会议地点 | Amer Univ Sharjah, Sharjah, U ARAB EMIRATES |
摘要 | This paper presents an online algorithm for mixture model-based clustering. Online algorithms allow data points to be processed sequentially, which is critical for real-time and large-scale applications. The proposed online algorithm is based on finite generalized Dirichlet (GD) mixtures together with a unsupervised localized feature selection scheme. By learning the proposed model in an online manner through a variational inference framework, all the involved model parameters, number of components and features weights are estimated simultaneously in closed forms. Additionally, the problem of overfitting is avoided due to the nature of Bayesian learning. The proposed method is validated by both synthetic data and an application concerning the online automatic image annotation. © 2013 IEEE. |
关键词 | generalized Dirichlet mixtures localized feature selection mixture model online learning variational Bayes |
DOI | 10.1109/ICCSPA.2013.6487242 |
URL | 查看来源 |
收录类别 | CPCI-S |
语种 | 英语English |
WOS研究方向 | Engineering ; Telecommunications |
WOS类目 | Engineering, Electrical & Electronic ; Telecommunications |
WOS记录号 | WOS:000318427600017 |
Scopus入藏号 | 2-s2.0-84876037720 |
引用统计 | |
文献类型 | 会议论文 |
条目标识符 | https://repository.uic.edu.cn/handle/39GCC9TT/13299 |
专题 | 个人在本单位外知识产出 理工科技学院 |
通讯作者 | Fan, Wentao |
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. An online approach for learning non-Gaussian mixture models with localized feature selection[C], 2013. |
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