# ASSET: APPROXIMATE STOCHASTIC SUBGRADIENT ESTIMATION TRAINING FOR SUPPORT VECTOR MACHINES

### Sangkyun Lee, Stephen Wright

#### Abstract

Subgradient methods for training support vector machines have been quite successful for solving large-scale and online learning problems. However, they have been restricted to linear kernels and strongly convex formulations. This paper describes efficient subgradient approaches without such limitations, making use of randomized low-dimensional approximations to nonlinear kernels, and minimization of a reduced primal formulation using an algorithm based on robust stochastic approximation, which do not require strong convexity.

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#### Paper Citation

#### in Harvard Style

Lee S. and Wright S. (2012). **ASSET: APPROXIMATE STOCHASTIC SUBGRADIENT ESTIMATION TRAINING FOR SUPPORT VECTOR MACHINES** . In *Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,* ISBN 978-989-8425-98-0, pages 223-228. DOI: 10.5220/0003786202230228

#### in Bibtex Style

@conference{icpram12,

author={Sangkyun Lee and Stephen Wright},

title={ASSET: APPROXIMATE STOCHASTIC SUBGRADIENT ESTIMATION TRAINING FOR SUPPORT VECTOR MACHINES},

booktitle={Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},

year={2012},

pages={223-228},

publisher={SciTePress},

organization={INSTICC},

doi={10.5220/0003786202230228},

isbn={978-989-8425-98-0},

}

#### in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,

TI - ASSET: APPROXIMATE STOCHASTIC SUBGRADIENT ESTIMATION TRAINING FOR SUPPORT VECTOR MACHINES

SN - 978-989-8425-98-0

AU - Lee S.

AU - Wright S.

PY - 2012

SP - 223

EP - 228

DO - 10.5220/0003786202230228