One-pass online learning: A local approach
作者:
Highlights:
• Propose an one-pass local online learning algorithm (LOL).
• LOL learns multiple hyperplanes jointly.
• LOL makes non-linear online learning more effective and accurate.
• Provide theoretical analysis on the cumulative error of LOL.
• Experimentally show the effectiveness of the proposed method.
摘要
Highlights•Propose an one-pass local online learning algorithm (LOL).•LOL learns multiple hyperplanes jointly.•LOL makes non-linear online learning more effective and accurate.•Provide theoretical analysis on the cumulative error of LOL.•Experimentally show the effectiveness of the proposed method.
论文关键词:One-pass online learning,Local modeling,Classification
论文评审过程:Received 13 January 2015, Revised 25 May 2015, Accepted 1 September 2015, Available online 15 September 2015, Version of Record 27 November 2015.
论文官网地址:https://doi.org/10.1016/j.patcog.2015.09.003