Sparse Passive-Aggressive learning for bounded online kernel methods

• Main Authors: LU, Jing, SAHOO, Doyen, ZHAO, Peilin, HOI, Steven C. H.
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2018
• Subjects: Kernel methods; Online learning; Online multiple-kernel learning; Databases and Information Systems; Numerical Analysis and Scientific Computing; Theory and Algorithms
• Online Access: https://ink.library.smu.edu.sg/sis_research/3999; https://ink.library.smu.edu.sg/context/sis_research/article/5001/viewcontent/sparse.pdf
• Institution: Singapore Management University

One critical deficiency of traditional online kernel learning methods is their unbounded and growing number of support vectors in the online learning process, making them inefficient and non-scalable for large-scale applications. Recent studies on scalable online kernel learning have attempted to ov...