Locality-constrained max-margin sparse coding

作者：

Highlights：

• Devise a locality-constrained max-margin sparse coding (LC-MMSC) framework.

• Use both labeled and unlabeled data to construct classification model.

• Provide theoretical analysis on the convergence of the proposed LC-MMSC.

• The proposed LC-MMSC outperforms other comparison algorithms on three datasets.

摘要

Highlights•Devise a locality-constrained max-margin sparse coding (LC-MMSC) framework.•Use both labeled and unlabeled data to construct classification model.•Provide theoretical analysis on the convergence of the proposed LC-MMSC.•The proposed LC-MMSC outperforms other comparison algorithms on three datasets.

论文关键词：Locality,Sparse Coding,Max-margin

论文评审过程：Received 21 June 2016, Revised 25 October 2016, Accepted 14 December 2016, Available online 19 December 2016, Version of Record 14 January 2017.

论文官网地址：https://doi.org/10.1016/j.patcog.2016.12.015