Two-Layer Multiple Kernel Learning

• Main Authors: ZHUANG, JInfeng, TSANG, Ivor W., HOI, Steven C. H.
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2011
• Subjects: Benchmark datasets; Classification tasks; Generalization performance; Kernel machine; Machine learning problem; Multilayer structures; Computer Sciences; Databases and Information Systems; Theory and Algorithms
• Online Access: https://ink.library.smu.edu.sg/sis_research/2293; https://ink.library.smu.edu.sg/context/sis_research/article/3293/viewcontent/ChuS2011zhuang11a.pdf
• Institution: Singapore Management University

Multiple Kernel Learning (MKL) aims to learn kernel machines for solving a real machine learning problem (e.g. classification) by exploring the combinations of multiple kernels. The traditional MKL approach is in general “shallow” in the sense that the target kernel is simply a linear (or convex) co...