Totally-Corrective Multi-class Boosting
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Altmetric Citations
Hao, Zhihui; Shen, Chunhua; Barnes, Nick; Wang, Bo
Description
We proffer totally-corrective multi-class boosting algorithms in this work. First, we discuss the methods that extend two-class boosting to multi-class case by studying two existing boosting algorithms: AdaBoost.MO and SAMME, and formulate convex optimization problems that minimize their regularized cost functions. Then we propose a column-generation based totally-corrective framework for multi-class boosting learning by looking at the Lagrange dual problems. Experimental results on UCI...[Show more]
Collections | ANU Research Publications |
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Date published: | 2010 |
Type: | Conference paper |
URI: | http://hdl.handle.net/1885/62216 |
Source: | Proceedings of ACCV 2010 |
DOI: | 10.1007/978-3-642-19282-1_22 |
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01_Hao_Totally-Corrective_Multi-class_2010.pdf | 246.03 kB | Adobe PDF | Request a copy |
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