Robust regularized Kernel regression

Robust regression techniques are critical to fitting data with noise in real-world applications. Most previous work of robust kernel regression is usually formulated into a dual form, which is then solved by some quadratic program solver consequently. In this correspondence, we propose a new formula...

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Bibliographic Details
Main Authors: ZHU, Jianke, HOI, Steven C. H., LYU, Michael R.
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2008
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Online Access:https://ink.library.smu.edu.sg/sis_research/2316
https://ink.library.smu.edu.sg/context/sis_research/article/3316/viewcontent/RobustRegularized_2008.pdf
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Institution: Singapore Management University
Language: English