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Online prediction of time series data with recurrent kernels

  • Zhao Xu
  • , Qing Song
  • , Fan Haijin
  • , Danwei Wang

科研成果: 书/报告/会议事项章节会议稿件同行评审

4 引用 (Scopus)

摘要

We propose a robust recurrent kernel online learning (RRKOL) algorithm which allows the exploitation of the kernel trick in an online fashion. The novel RRKOL algorithm achieves guaranteed weight convergence with regularized risk management through the recurrent hyper-parameters for a superior generalization performance. To select useful data to be learned and remove redundant ones, a sparcification procedure is developed based on the stability analysis of the system. Two time-series prediction examples are presented.

源语言英语
主期刊名2012 International Joint Conference on Neural Networks, IJCNN 2012
DOI
出版状态已出版 - 2012
已对外发布
活动2012 Annual International Joint Conference on Neural Networks, IJCNN 2012, Part of the 2012 IEEE World Congress on Computational Intelligence, WCCI 2012 - Brisbane, QLD, 澳大利亚
期限: 10 6月 201215 6月 2012

出版系列

姓名Proceedings of the International Joint Conference on Neural Networks

会议

会议2012 Annual International Joint Conference on Neural Networks, IJCNN 2012, Part of the 2012 IEEE World Congress on Computational Intelligence, WCCI 2012
国家/地区澳大利亚
Brisbane, QLD
时期10/06/1215/06/12

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