| Transfer latent variable model based on divergence analysis | |
| Gao, Xinbo2; Wang, Xiumei2; Li, Xuelong1; Tao, Dacheng3 | |
| 作者部门 | 光学影像分析与学习中心 |
| 2011-10-01 | |
| 发表期刊 | PATTERN RECOGNITION
 |
| ISSN | 0031-3203 |
| 卷号 | 44期号:10-11页码:2358-2366 |
| 摘要 | Latent variable models are powerful dimensionality reduction approaches in machine learning and pattern recognition. However, this kind of methods only works well under a necessary and strict assumption that the training samples and testing samples are independent and identically distributed. When the samples come from different domains, the distribution of the testing dataset will not be identical with the training dataset. Therefore, the performance of latent variable models will be degraded for the reason that the parameters of the training model do not suit for the testing dataset. This case limits the generalization and application of the traditional latent variable models. To handle this issue, a transfer learning framework for latent variable model is proposed which can utilize the distance (or divergence) of the two datasets to modify the parameters of the obtained latent variable model. So we do not need to rebuild the model and only adjust the parameters according to the divergence, which will adopt different datasets. Experimental results on several real datasets demonstrate the advantages of the proposed framework. (C) 2010 Elsevier Ltd. All rights reserved. |
| 文章类型 | Article |
| 关键词 | Dimensionality Reduction Latent Variable Model Transfer Learning Bregman Divergence |
| WOS标题词 | Science & Technology ; Technology |
| DOI | 10.1016/j.patcog.2010.06.013 |
| 收录类别 | SCI ; EI |
| 关键词[WOS] | NONLINEAR DIMENSIONALITY REDUCTION ; PRINCIPAL COMPONENT ANALYSIS ; FRAMEWORK |
| 语种 | 英语 |
| WOS研究方向 | Computer Science ; Engineering |
| WOS类目 | Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic |
| WOS记录号 | WOS:000292849000014 |
| 引用统计 | |
| 文献类型 | 期刊论文 |
| 条目标识符 | http://ir.opt.ac.cn/handle/181661/10179 |
| 专题 | 光谱成像技术研究室 |
| 作者单位 | 1.Chinese Acad Sci, Xian Inst Opt & Precis Mech, State Key Lab Transient Opt & Photon, Ctr OPT IMagery Anal & Learning OPTIMAL, Xian 710119, Shaanxi, Peoples R China 2.Xidian Univ, Sch Elect Engn, Xian 710071, Peoples R China 3.Nanyang Technol Univ, Sch Comp Engn, Singapore 639798, Singapore |
| 推荐引用方式 GB/T 7714 | Gao, Xinbo,Wang, Xiumei,Li, Xuelong,et al. Transfer latent variable model based on divergence analysis[J]. PATTERN RECOGNITION,2011,44(10-11):2358-2366. |
| APA | Gao, Xinbo,Wang, Xiumei,Li, Xuelong,&Tao, Dacheng.(2011).Transfer latent variable model based on divergence analysis.PATTERN RECOGNITION,44(10-11),2358-2366. |
| MLA | Gao, Xinbo,et al."Transfer latent variable model based on divergence analysis".PATTERN RECOGNITION 44.10-11(2011):2358-2366. |
| 条目包含的文件 | ||||||
| 文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
| Transfer latent vari（659KB） | 期刊论文 | 出版稿 | 限制开放 | CC BY-NC-SA | 请求全文 | |
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