# Sequential Minimal Optimization : A Fast Algorithm for Training Support Vector Machines

@article{Platt1998SequentialMO, title={Sequential Minimal Optimization : A Fast Algorithm for Training Support Vector Machines}, author={John Platt}, journal={Microsoft Research Technical Report}, year={1998} }

This paper proposes a new algorithm for training support vector machines: Sequential Minimal Optimization, or SMO. Training a support vector machine requires the solution of a very large quadratic programming (QP) optimization problem. SMO breaks this large QP problem into a series of smallest possible QP problems. These small QP problems are solved analytically, which avoids using a time-consuming numerical QP optimization as an inner loop. The amount of memory required for SMO is linear in… CONTINUE READING

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