Patent · US Active

Proximal gradient method for huberized support vector machine

US10332025B2 · kind B2 · utility

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2References

20Claims

0Family size

Assignee

Siemens Aktiengesellschaft · DE

Inventors

Yangyang Xu · 安丰镇, CN
Ioannis Akrotirianakis · Plainsboro, US
Amit Chakraborty · Plainsboro, US

Key dates

Filing date	Mar 10, 2015
Grant date	Jun 25, 2019
Priority date	—
Expiry date	Nov 18, 2036

Classification

Technology area (CPC G)Physics
CPC primaryG06N20/00
WIPO fieldComputer technology
WIPO sectorElectrical engineering

Abstract

The Support Vector Machine (SVM) has been used in a wide variety of classification problems. The original SVM uses the hinge loss function, which is nondifferentiable and makes the problem difficult to solve in particular for regularized SVMs, such as with l1-norm. The Huberized SVM (HSVM) is considered, which uses a differentiable approximation of the hinge loss function. The Proximal Gradient (PG) method is used to solving binary-class HSVM (BHSVM) and then generalized to multi-class HSVM (MHSVM). Under strong convexity assumptions, the algorithm converges linearly. A finite convergence result about the support of the solution is given, based on which the algorithm is further accelerated by a two-stage method.

Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.