Göm meny

Machine Learning

An ELLIIT PhD Course at Lund University, Lund, Sweden.


General Information

This course gives an introduction to machine learning, with a focus toward dynamical systems. To a large extent this involves probabilistic modelling in order to be able to solve a wide range of problems.

  • Lecture slides are available here.
  • Contents

    • Linear regression
    • Linear classification
    • Neural networks
    • Support vector machines
    • Gaussian processes
    • Expectation Maximization (EM)
    • Clustering
    • Approximate inference (VB and EP)
    • Introducing graphical models
    • Boosting
    • MCMC and sampling methods

    Organization and Examination

    This is an ELLIIT graduate course that is given in order to further strengthen the cooperation between Linköping and Lund.

    The course gives 6 hp (you can receive an additional 3 hp by carrying out a project).

    The examination consists in a written two day take home exam.

    Date and Time

    This is an intensive course and it will be given in two parts,

    • Part 1. May 25 - May 27, 2011
    • Part 2. June 7 - June 10, 2011

    Course Literature

    The main book used during the course is,
    [B] Christopher M. Bishop Pattern Recognition and Machine Learning, Springer, 2006.

    We will also make use of,
    [HTF] Trevor Hastie, Robert Tibshirani and Jerome Friedman The Elements of Statistical Learning: Data Mining, Inference and Prediction, Second edition, Springer, 2009.

    Prerequisites

    Basic undergraduate courses in linear algebra, statistics, signal and systems.

    Related Courses

    System identification, sensor fusion.

    Exam

    Standard 2 day (48 h) exam. The exam period is week 34 - 35 (August 22 - September 4). The exam can be collected from Eva Westin at the Department of Automatic Control.

    Contact Persons

    Dr Thomas Schön, tel +46 13 281373, email: schon_at_isy.liu.se.
    Prof. Bo Bernhardsson, tel +46 46 222 87 86, email: bob_at_control.lth.se.
    Prof. Rolf Johansson., tel +46 46 222 87 91, email: Rolf.Johansson_at_control.lth.se.

    Thomas Schön

    Associate Professor in Automatic Control

    Phone:
    +46 13 281373
    Mobile (private):
    +46 735 933 887
    E-mail:
    schon_at_isy.liu.se
    Address:
    Dept. of Electrical Engineering
    Linköping University
    SE-581 83 Linköping
    Sweden
    Visiting Address:
    Campus Valla
    Building B
    Room 2A:NNN (in the A corridor on the ground floor between entrance 25 and 27)


    Informationsansvarig: Thomas Schön
    Senast uppdaterad: 2012-10-13