Multi-class classification via discriminative multiple subspace learning
Tang, Tang; Qiao, Hong; Zheng, Suiwu; Tang, T
2013
会议名称International Conference on Mechatronic Sciences, Electric Engineering and Computer (MEC)
会议录名称PROCEEDINGS 2013 INTERNATIONAL CONFERENCE ON MECHATRONIC SCIENCES, ELECTRIC ENGINEERING AND COMPUTER (MEC)
会议日期DEC 20-22, 2013
会议地点Shenyang, PEOPLES R CHINA
摘要Subspace learning has long been a fundamental yet important problem of modeling data distributions. In this paper, we propose to learn multiple linear subspaces in a supervised way for multi-classclassification. To this end, a discriminative term redefining decision margin in terms of reconstruction error is incorporated into the model. The term enjoys similar properties of hinge loss function to the benefit of classification and leads to a training process seeking the balance between unsupervisedlearning and supervised learning. In the experiments on written digits dataset, our algorithm outperforms other methods proposed recently in both accuracy and computation efficiency.
关键词Subspace Learning Generative Model Discriminative Model
文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/12868
专题复杂系统管理与控制国家重点实验室_机器人理论与应用
通讯作者Tang, T
推荐引用方式
GB/T 7714
Tang, Tang,Qiao, Hong,Zheng, Suiwu,et al. Multi-class classification via discriminative multiple subspace learning[C],2013.
条目包含的文件
条目无相关文件。
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Tang, Tang]的文章
[Qiao, Hong]的文章
[Zheng, Suiwu]的文章
百度学术
百度学术中相似的文章
[Tang, Tang]的文章
[Qiao, Hong]的文章
[Zheng, Suiwu]的文章
必应学术
必应学术中相似的文章
[Tang, Tang]的文章
[Qiao, Hong]的文章
[Zheng, Suiwu]的文章
相关权益政策
暂无数据
收藏/分享
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。