Material Detail

Introduction to Kernel Methods

Introduction to Kernel Methods

This video was recorded at PASCAL Bootcamp in Machine Learning, Marseille 2010. In this talk, we are going to see the basics of kernels methods. After a brief presentation of a very simple kernel classifier, we'll give the definition of a postive definite kernel and explain Support vector machine learning. Then, a few kernels for structured data, namely sequences and graphs, will be described. The representer theorem is presented, which explains the rationale for the usual kernel expansion encountered when working with kernel methods. Finally, a few elements from statistical learning theory are given.

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.