Abstract
Sequential minimal optimization (SMO) algorithm is one of the simplest decomposition methods for learning of support vector machines (SVMs). Keerthi and Gilbert have recently studied the convergence property of SMO algorithm and given a proof that SMO algorithm always stops within a finite number of iterations. In this letter, we point out the incompleteness of their proof and give a more rigorous proof.
| Original language | English |
|---|---|
| Pages (from-to) | 774-776 |
| Number of pages | 3 |
| Journal | IEEE Transactions on Neural Networks |
| Volume | 16 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - May 1 2005 |
| Externally published | Yes |
Keywords
- Convergence
- Sequential minimal optimization (SMO) algorithm
- Support vector machines (SVMs)
- Termination
ASJC Scopus subject areas
- Software
- Computer Science Applications
- Computer Networks and Communications
- Artificial Intelligence
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Cite this
Takahashi, N., & Nishi, T. (2005). Rigorous proof of termination of SMO algorithm for support vector machines. IEEE Transactions on Neural Networks, 16(3), 774-776. https://doi.org/10.1109/TNN.2005.844857