Non-linear dictionary learning with partially labeled data
作者：
Highlights：
• A dictionary learning method that utilizes labeled and unlabeled data is proposed.
• Using kernel trick, the proposed formulation is extended to the non-linear case.
• An efficient optimization procedure is proposed for solving this non-linear problem.
• Each training sample can have multiple labels and only one of them is correct.
摘要
Highlights•A dictionary learning method that utilizes labeled and unlabeled data is proposed.•Using kernel trick, the proposed formulation is extended to the non-linear case.•An efficient optimization procedure is proposed for solving this non-linear problem.•Each training sample can have multiple labels and only one of them is correct.
论文关键词：Weakly supervised learning,Semi-supervised learning,Kernel methods,Dictionary learning,Classification
论文评审过程：Received 2 January 2014, Revised 24 July 2014, Accepted 31 July 2014, Available online 8 August 2014, Version of Record 16 July 2015.
论文官网地址：https://doi.org/10.1016/j.patcog.2014.07.031
