MKBoost: A framework of multiple kernel boosting

• Main Authors: XIA, Hao, HOI, Steven C. H.
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2013
• Subjects: Multiple kernel learning; boosting; classification; kernel methods; Computer Sciences; Databases and Information Systems; Numerical Analysis and Scientific Computing
• Online Access: https://ink.library.smu.edu.sg/sis_research/2280; https://ink.library.smu.edu.sg/context/sis_research/article/3280/viewcontent/MKBoost_A_Framework_of_Multiple_Kernel_Boosting.pdf
• Institution: Singapore Management University

Multiple kernel learning (MKL) is a promising family of machine learning algorithms using multiple kernel functions for various challenging data mining tasks. Conventional MKL methods often formulate the problem as an optimization task of learning the optimal combinations of both kernels and classif...