Lectures

Tuesday Feb 12 Introduction: course outline, basic terms and notation, list of readings
- Class Slides: (pdf)
Feb 13 Optimization Theory
- Class Slides_1: (pdf)
- Class Slides_2: (pdf)
  Other useful Opt. slides (K. Tretyakov & T. de Bie)
Feb 19,20 Kernel Methods
- Class Slides: (pdf)
  Other helpful slides (Campbell)
  More helpful slides
Feb 26,27 Support Vector Machines
- Class Slides: (pdf)
  Other helpful slides, SVMs by Ron Meir
  Some more helpful slides
No class on March 4th
Mar 5 Implementing SVMs [Konstantin]
- Class Slides: (pdf)
Mar 11 Support Vector Regression
- Class Slides: (pdf)
Mar 12 Semi-supervised SVR & Ranking
- Class Slides - SemiSVR: (pdf)
- Class Slides - Ranking - Updated!! (pdf)
Mar 18 Evaluating your results and Writing
- Class Slides (pdf)
Mar 19 Nu SVMs
- Class Slides - (pdf)
Mar 25 Boosting
- Class Slides - Agius (pdf)
- Class Slides - Freund (pdf)
Mar 26 Principal Component Analysis
- Class Slides (pdf)
Apr 1 Clustering
- Class Slides (pdf)
Apr 2 MulliVelled - Educational computer game (4pm, Liivi 311)
Review for exam at 5pm in 402
Geometric inperpretation for SVR in relation to Sasha's question

Apr 8 Exam 1

Apr 15 Spectral Clustering
- Class Slides (pdf)
Apr 22 Manifold learning
- Class Slides (pdf)
Apr 22 Novelty detection + Meelis Presentation
- Class Slides (pdf)
Apr 23,29 Probabilistic Modeling
- Class Slides Part 1 (pdf)
- Slides Part 2 Graphical Models
- Slides Part 3 - A practical application (pdf)

Apr 30 Active learning + Liina Presentation
- HMMs (pdf)
- Active learning - intro (pdf)
May 6 Fisher Kernel
- Fishy slides (pdf)
May 7 Data Fusion + Priit's presentation
- Yeast protein function prediction (pdf)
May 13 Multi-task Learning
- Class slides (pdf)
May 14 KCCA - Roland's presentation