Robust Semi-Supervised Growing Self-Organizing Map

作者：

Highlights：

• Defining a new cost function for robust online Semi-Supervised GSOM.

• Using half quadratic technique to solve a robust online Semi-Supervised GSOM.

• Using an adaptive method to adjust robust online semi-supervised GSOM parameters.

摘要

•Defining a new cost function for robust online Semi-Supervised GSOM.•Using half quadratic technique to solve a robust online Semi-Supervised GSOM.•Using an adaptive method to adjust robust online semi-supervised GSOM parameters.

论文关键词：Semi-supervised learning,Online learning,Dynamic self-organization network,Adaptive learning,Half quadratic

论文评审过程：Received 14 October 2017, Revised 22 March 2018, Accepted 23 March 2018, Available online 26 March 2018, Version of Record 24 April 2018.

论文官网地址：https://doi.org/10.1016/j.eswa.2018.03.046