ν-Structured 서포트 벡터 머신을 이용한 음성 인식기 훈련

Abstract

In this paper, we propose ν-structured support vector machine(ν -SSVM), an extension of  -support vector machine(ν -SVM) to structured prediction problems. The proposed ν-SSVM is modified from the structured SVM(SSVM) to have both advantages of the intuitive parameter ν in the ν-SVM and the margin scaling in the SSVM. In the ν-SSVM, ν asymptotically equals the empirical risk over support vectors. The stochastic subgradient descent is used to solve the optimization problem of the ν-SSVM.