Scalable online kernel learning

• Main Author: LU, Jing
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2017
• Subjects: machine learning; online learning; kernel learning; classification; kernel approximation; scalable learning; Databases and Information Systems; Theory and Algorithms
• Online Access: https://ink.library.smu.edu.sg/etd_coll/142; https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=1141&context=etd_coll
• Institution: Singapore Management University

One critical deficiency of traditional online kernel learning methods is their increasing and unbounded number of support vectors (SV’s), making them inefficient and non-scalable for large-scale applications. Recent studies on budget online learning have attempted to overcome this shortcoming by bou...