These are the archived web pages of the spring 2007 course.
The contents of this course vary yearly. The next course will probably
take place in spring 2008. Please
for current information.
|Instructor||Kai Puolamäki, PhD|
|Course assistant||Mikko Korpela, MSc|
|Course format||Seminar course|
|Semester||Spring 2007 (during periods III and IV)|
|Seminar sessions||On Mondays at 14–16 in lecture
hall T4 in the computer science building|
Konemiehentie 2, Otaniemi, Espoo
The seminar course will provide a comprehensive introduction to the fields of pattern recognition and machine learning. The course is especially suitable for advanced undergraduates and PhD students who want to have (or refresh) a comprehensive and solid overview of these fields.
To pass the course, you must:
To pass with distinction, you should additionally:
Estimate of time usage (5 cr equals approximately 133 hours of working time for a typical student):
The course is based on the following book:
Information on how to get the book.
The schedule follows the structure of the course book. At each seminar session, one chapter of the book is presented. Below, you can find the PDF slides of the seminar lectures by the students. (Notice that the presentations below have been prepared and given by the students, who also may or may not have the source files (LaTeX, PowerPoint etc.) for the PDF slides. The lecturer does not have the source files.)
|Jan 15||Organization of the course||Kai Puolamäki||Slides (PDF)|
|Jan 22||Probability Distributions||Mikko Korpela||Slides (PDF)||A condensed introduction to the exponential family notation (including Bernoulli, Multinomial, Gaussian etc. distributions) is given by subsection 3.1 of Buntine ECML'02. Rest of the section 3, "Background Theory", covers the EM and variational approaches.|
|Jan 29||Linear Models for Regression||Nicolau Gonçalves||Slides (PDF)|
|Feb 5||Linear Models for Classification||Teemu Mutanen
Slides 1 with comments (PDF)
Slides 2 (PDF)
|Feb 12||Neural Networks||Tino Ojala
|Feb 19||Kernel Methods||Jayaprakash Rajasekharan||Slides (PDF)|
|Feb 26||Sparse Kernel Machines||Janne Argillander||Slides (PDF)|
|Mar 5||No lecture (exam period)|
|Mar 12||Graphical Models||Dmitrij Lagutin||Slides (PDF)|
|Mar 19||Mixture Models and EM||Yoan Miche||Slides (PDF)|
|Mar 26||Approximate Inference||Janne Toivola
|Slides 1 (PDF)
Slides 2 (PDF)
|Apr 2||Sampling Methods||Matti Pöllä||Slides (PDF)|
|Apr 9||No lecture (easter break)|
|Apr 16||Continuous Latent Variables||Mikaela Klami||Slides (PDF)|
|Apr 23||Sequential Data||Mari-Sanna Paukkeri||Slides (PDF)|
|Apr 30||Combining Models||Jukka Parviainen||Slides (PDF)|
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