题名 | Variational Learning for Finite Generalized Inverted Dirichlet Mixture Models with a Component Splitting Approach |
作者 | |
发表日期 | 2019-06-01 |
会议名称 | 28th IEEE International Symposium on Industrial Electronics (IEEE-ISIE) |
会议录名称 | IEEE International Symposium on Industrial Electronics
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ISBN | 9781728136660 |
卷号 | 2019-June |
页码 | 1453-1458 |
会议日期 | JUN 12-14, 2019 |
会议地点 | Vancouver, CANADA |
摘要 | Mixture models play a crucial role in pattern recognition methods based on clustering. In this paper, we propose a finite generalized inverted Dirichlet mixture model with a variational learning method for parameter estimation. The highlight of our model is the component splitting approach which handles the problem of model selection in an incremental fashion within the variational framework. Efficiency of proposed model is tested for image categorization tasks. |
关键词 | Component Splitting Mixture Models Unsupervised Learning Variational Inference |
DOI | 10.1109/ISIE.2019.8781300 |
URL | 查看来源 |
收录类别 | CPCI-S |
语种 | 英语English |
WOS研究方向 | Engineering |
WOS类目 | Engineering, Electrical & Electronic |
WOS记录号 | WOS:000500998700217 |
Scopus入藏号 | 2-s2.0-85070597491 |
引用统计 | |
文献类型 | 会议论文 |
条目标识符 | https://repository.uic.edu.cn/handle/39GCC9TT/13059 |
专题 | 个人在本单位外知识产出 理工科技学院 |
作者单位 | 1.Concordia Institute for Information Systems Engineering,Concordia University,Montreal,H3G 1M8,Canada 2.College of Computer Science and Technology,Huaqiao University,Xiamen,361021,China |
推荐引用方式 GB/T 7714 | Maanicshah, Kamal,Bouguila, Nizar,Fan, Wentao. Variational Learning for Finite Generalized Inverted Dirichlet Mixture Models with a Component Splitting Approach[C], 2019: 1453-1458. |
条目包含的文件 | 条目无相关文件。 |
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