Multi-class classification via discriminative multiple subspace learning
文献类型:会议论文
作者 | Tang, Tang![]() ![]() ![]() |
出版日期 | 2013 |
会议名称 | 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 |
关键词 | subspace learning generative model discriminative model |
通讯作者 | Tang, T |
英文摘要 | 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. |
会议录 | PROCEEDINGS 2013 INTERNATIONAL CONFERENCE ON MECHATRONIC SCIENCES, ELECTRIC ENGINEERING AND COMPUTER (MEC)
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源URL | [http://ir.ia.ac.cn/handle/173211/12868] ![]() |
专题 | 自动化研究所_复杂系统管理与控制国家重点实验室_机器人应用与理论组 |
推荐引用方式 GB/T 7714 | Tang, Tang,Qiao, Hong,Zheng, Suiwu. Multi-class classification via discriminative multiple subspace learning[C]. 见:International Conference on Mechatronic Sciences, Electric Engineering and Computer (MEC). Shenyang, PEOPLES R CHINA. DEC 20-22, 2013. |
入库方式: OAI收割
来源:自动化研究所
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