SimpleSVM
Vishwanathan, S.V.N.; Smola, Alexander; Murty, M. Narasimha
Description
We present a fast iterative support vector training algorithm for a large variety of different formulations. It works by incrementally changing a candidate support vector set using a greedy approach, until the supporting hyperplane is found within a finite number of iterations. It is derived from a simple active set method which sweeps through the set of Lagrange multipliers and keeps optimality in the unconstrained variables, while discarding large amounts of bound-constrained variables. The...[Show more]
Collections | ANU Research Publications |
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Date published: | 2003 |
Type: | Conference paper |
URI: | http://hdl.handle.net/1885/88642 |
Source: | Proceedings of the Twentieth International Conference on Machine Learning |
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File | Description | Size | Format | Image |
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01_Vishwanathan_SimpleSVM_2003.pdf | 404.6 kB | Adobe PDF | Request a copy |
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