Material Detail

Stochastic Subgradient Approach for Solving Linear Support Vector Machines

Stochastic Subgradient Approach for Solving Linear Support Vector Machines

This video was recorded at Slovenian KDD Conference on Data Mining and Data Warehouses (SiKDD), Ljubljana 2008. This paper is an overview of a recent approach for solving linear support vector machines (SVMs), the PEGASOS algorithm. The algorithm is based on a technique called the stochastic subgradient descent and employs it for solving the optimization problem posed by the soft margin SVM - a very popular classifier. We briefly introduce the SVM problem and one of the widely used solvers, SVM light, then describe the PEGASOS algorithm and present some experiments. We conclude that the algorithm efficiently discovers suboptimal solutions to large scale problems within a matter of seconds.

Quality

  • User Rating
  • Comments
  • Learning Exercises
  • Bookmark Collections
  • Course ePortfolios
  • Accessibility Info

More about this material

Comments

Log in to participate in the discussions or sign up if you are not already a MERLOT member.