Incremental p-margin algorithm for classification with arbitrary norm
作者：
Highlights：
• We propose a novel algorithm for large p-margin classification problems, for 1≤p≤∞.
• The approach is based on an unified perceptron-based formulation.
• Soft-margin in primal variables is introduced for non-linearly separable problems.
• An efficient incremental strategy is used to construct the large p-margin solution.
摘要
Highlights•We propose a novel algorithm for large p-margin classification problems, for 1≤p≤∞.•The approach is based on an unified perceptron-based formulation.•Soft-margin in primal variables is introduced for non-linearly separable problems.•An efficient incremental strategy is used to construct the large p-margin solution.
论文关键词：Large margin classifiers,p-Norm,Perceptron algorithms,Binary classification
论文评审过程：Received 12 September 2015, Revised 9 January 2016, Accepted 19 January 2016, Available online 29 January 2016, Version of Record 21 March 2016.
论文官网地址：https://doi.org/10.1016/j.patcog.2016.01.016
