Semi-supervised double sparse graphs based discriminant analysis for dimensionality reduction

作者：

Highlights：

• Semi-supervised double sparse graphs are explored.

• Joint k-nearest-neighbor selection strategy is proposed.

• Two different semi-supervised dimensionality reduction methods are proposed.

摘要

Highlights•Semi-supervised double sparse graphs are explored.•Joint k-nearest-neighbor selection strategy is proposed.•Two different semi-supervised dimensionality reduction methods are proposed.

论文关键词：Semi-supervised learning,Discriminant analysis,Dimensionality reduction,Sparse graph,Graph embedding

论文评审过程：Received 15 July 2015, Revised 10 August 2016, Accepted 11 August 2016, Available online 13 August 2016, Version of Record 25 August 2016.

论文官网地址：https://doi.org/10.1016/j.patcog.2016.08.010