A0491
Title: Analysis of online learning algorithms
Authors: Zheng-Chu Guo - Zhejiang University (China) [presenting]
Abstract: Analyzing and processing large-scale data sets is becoming ubiquitous in the era of big data. Online learning algorithms have attracted increasing interest in recent years due to their low computational complexity and storage requirements. They have been applied to various learning tasks. Unlike batch learning, which processes the whole sample once, online learning processes the sample one by one and updates the output in time. We will give some mathematical analysis of online learning algorithms in a reproducing kernel Hilbert space (RKHS) for handling large-scale data.
