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Manifold mapping learning by regression tree boosting
Chen XA(陈希爱); Han Z(韩志); Tang YD(唐延东)
作者部门机器人学研究室
会议名称2015 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER)
会议日期June 8-12, 2015
会议地点Shenyang, China
会议录名称2015 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER)
出版者IEEE
出版地Piscataway, NJ, USA
2015
页码1579-1583
收录类别EI ; CPCI(ISTP)
EI收录号20161402187705
WOS记录号WOS:000380502300288
产权排序1
ISSN号2379-7711
ISBN号978-1-4799-8730-6
摘要Manifold learning has shown powerful information processing capability for high-dimensional data. In this paper, we proposed a manifold mapping learning algorithm to alleviate the shortage of traditional methods and broaden the applications of manifold learning. The mapping is achieved by using the regression tree boosting, which is a strong ensemble learner composed by a group of regression trees as weak learners in the way of L2Boost. A set of verification experiments are conducted on both synthetic and real-world data sets. And the results have demonstrated that the algorithm can perform well on both regression and prediction applications.
语种英语
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文献类型会议论文
条目标识符http://ir.sia.cn/handle/173321/17476
专题机器人学研究室
作者单位1.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China
2.University of Chinese Academy of Sciences, Beijing, China
推荐引用方式
GB/T 7714
Chen XA,Han Z,Tang YD. Manifold mapping learning by regression tree boosting[C]. Piscataway, NJ, USA:IEEE,2015:1579-1583.
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