摘要
Analysing and processing massive data is becoming ubiquitous in the era of big data.Distributed learning based on divide-and-conquer approach has attracted increasing interest in recent years,since it not only reduces computational complexity and storage require-ments,but also protects the data privacy when data subsets are distributively stored on different local machines.This paper provides a comprehensive review for distributed learning with parametric models,non-parametric models and other popular models.
作者简介
CONTACT:Zheng-Chu Guo,guozhengchu@zju.edu.cn。
