MTAT.03.228 Machine Learning Seminar

  • Course ID: MTAT.03.228
  • Seminars: Tuesday 4pm, Liivi 2-402
  • Credits: 3 credits (AP) , (4.5 Bologna)
  • Lecturer: Phaedra Agius, PhD
  • Questions: phaedragius at gmail dot com
    (Phaedra.Agius at ut dot ee) or Jaak.Vilo at ut.ee
  • Web: http://courses.cs.ut.ee/2008/mls

Machine learning is concerned with the development of efficient learning algorithms that perform well on novel data. With the masses of data available in today's world, the implementation of such algorithms together with a rigorous statistical validation of those methods is essential.

The goal of this seminar is familiarize you with a particular area of machine learning that is of interest to you or that is of use to your work. You will have the opportunity to use a machine learning strategy for your research by way of a project. The seminar will culminate in a TWO DAY CONFERENCE at the end of the semester during which you will present your project work.

The Machine Learning course running parallel to this seminar is a good source of information and reading material. You may access the website at http://courses.cs.ut.ee/2008/ml/ where you will find suggested reading and presentation slides.

The weekly Tuesday meetings at 4pm are informal and non-obligatory, their purpose being for you to seek out my guidance and advice on your work. However, your attendance on the following dates is mandatory.

February 26 Project Proposal
March 18 Project Plan
April 15 Project Progress Report 1
May 6 Project Progress Report 2

May 20 Project Paper due
May 20-25 Paper Review week
May 25 Paper reviews due

May 28, 4pm onwards - Conference
May 28, Final paper due

The online paper submission deadline will be on May 11. Your peers and myself will review the papers with constructive criticisms (guidelines will be provided prior to submission date, so that you can use those guidelines to help you write your paper). You will receive those reviews a few days before your conference presentation so that you will have the opportunity to tailor your presentation accordingly. Your final paper will be due on May 29.

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