List and Schedule of Reading Presentations here:

Feb 19 Presented by Kaur Alasoo
Introduction to Optimization Methods: a Brief Survey of Methods

Feb 26 Presented by Laur Tooming
Fast String Kernels using Inexact Matching for Protein Sequences

  • Presentation Slides: (pdf)

Mar 11 Presented by Jürgen Jänes
SVM-Fold: a tool for discriminative multi-class protein fold and superfamily recognition

  • Presentation Slides: (pdf)

Mar 12 Presented by me
A Semi-Supervised Regression Model for Mixed Numerical and Categorical Variables

  • Presentation Slides: Refer to Mar 11 lecture

Mar 18 Presented by Andres Tiko
On Comparing Classifiers: Pitfalls to Avoid and a Recommended Approach, S. Salzberg

  • Presentation Slides: (pdf)

Mar 19 Presented by Anastassia Semjonova
Optimizing Search Engines using Clickthrough Data

Mar 25 Presented by Aivi Kaljuvee
An efficient boosting algorithm for combining preferences, Y. Freund, R. Iyer, R. Schapire and Y. Singer

  • Presentation Slides: (pdf)

Mar 26 Presented by Aleksandr Tkatšenko
The Effect of Principal Component Analysis on Machine Learning Accuracy with High Dimensional Spectral Data

  • Presentation Slides: (pdf)

Apr 1 Presented by Sander Sõnajalg
A sober look at clustering stability

  • Presentation Slides: (pdf)

Apr 15 Presented by Nikita Shipilov
Functional Grouping of Genes Using Spectral Clustering and Gene Ontology

  • Presentation Slides: (pdf)

Apr 22 Presented by Meelis Kull
A Linear Programming Approach to Novelty Detection
Colin Campbell and Kristin Bennett

  • Presentation Slides: (pdf)

May 6 Presented by Liina Kamm
Active Learning in the Drug Discovery Process

  • Presentation Slides: (pdf)

May 7 Presented by Priit Adler
Kernel-based data fusion for gene prioritization

  • Presentation Slides: (pdf)

May 14 Presented by Roland Pihlakas
Finding Language-Independent Semantic Representation of Text Using Kernel Canonical Correlation Analysis

  • Presentation Slides: (pdf)
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