Efficient Structured Support Vector Regression
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Jia, Ke; Wang, Lei; Liu, Nianjun
Description
Support Vector Regression (SVR) has been a long standing problem in machine learning, and gains its popularity on various computer vision tasks. In this paper, we propose a structured support vector regression framework by extending the max-margin principle to incorporate spatial correlations among neighboring pixels. The objective function in our framework considers both label information and pairwise features, helping to achieve better cross-smoothing over neighboring nodes. With the bundle...[Show more]
Collections | ANU Research Publications |
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Date published: | 2010 |
Type: | Conference paper |
URI: | http://hdl.handle.net/1885/21117 |
Source: | Proceedings of the International Image and Vision Computing New Zealand Conference (IVCNZ 2010) |
DOI: | 10.1007/978-3-642-19318-7_46 |
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01_Jia_Efficient_Structured_Support_2010.pdf | 1.66 MB | Adobe PDF | Request a copy |
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