This course represents half of Advanced Topics in Machine Learning (aka COMP GI13 / COMP M050) from the UCL CS MSc on Machine Learning. The other half is an Introduction to Statistical Learning Theory, taught by Carlo Ciliberto.

Course announcements will be posted on the mailing list.

This page will contain slides and detailed notes for the kernel part of the course. The assignment may also be found here (at the bottom of the page). Note that the slides will be updated as the course progresses, and I modify them to answer questions I get in the classes. I'll put the date of last update next to each document - be sure to get the latest one. Let me know if you find errors.

There are sets of practice exercises and solutions further down the page (after the slides).

For questions on the course material, please email Heishiro Kanagawa.

Slides and notes

Lectures 1 and 2 slides and notes, last modified 17 Oct 2018

Lecture 3 slides (notes same as for lectures 1 and 2), last modified 17 Oct 2018

Lectures 4, 5 slides and notes, last modified 17 October 2018

Lectures 6, 7, 8 slides and notes, last modified 07 Nov 2017

Lecture 9 slides and notes, last modified 15 March 2016

Lecture 10 Slides, last modified 13 Dec 2017

Theory lectures Slides 1, Slides 2 , and notes, last modified 20 Mar 2013

Supplementary lecture slides, last modified 22 Mar 2012


The assignment (first part due in on 23 November 2018). You will need this extract on incomplete Cholesky (scanned from Shawe-Taylor and Cristianini, Kernel Methods for Pattern Analysis). Last modified 15 September 2018.

Practice exercises and solutions

The exercises are taken from exams in previous years, with minor modifications. Worked solutions are provided. Last modified 18 Oct 2015.
  • Set 1
  • Set 2
  • Contact