Gayle Leen I'm a postdoctoral researcher at the Statistical Machine Learning and Bioinformatics research group at the Laboratory of Computer and Information Science. My research interests include Bayesian methods, in particularly nonparametric methods (Gaussian processes, Dirichlet processes), generative models of data fusion, and their application to bioinformatics problems.

Contact information

Mail address:	Helsinki University of Techonology Laboratory of Computer and Information Science P.O. Box 5400 FIN-02015 HUT FINLAND
Location:	Computer Science Building Konemiehentie 2, Espoo Room A323
E-Mail:	gleen (at) cis.hut.fi

Selected publications

• G. Leen, D. Hardoon and S. Kaski. Automatic Choice of Control Measurements, 1st Asian Conference in Machine Learning (ACML), 2009. pdf

• G. Leen and C. Fyfe. Learning shared and separate features of two related data sets using GPLVM's. Poster in the NIPS 2008 Learning from Multiple Sources Workshop, December 13, Whistler, Canada. pdf

• G. Leen and C. Fyfe. Dirichlet process mixture models for finding shared structure between two related data sets, AIKED 08. pdf

• G. Leen and C. Fyfe. A Gaussian Process Latent Variable Model Formulation of Canonical Correlation Analysis. Pages 413-418 of: Proceedings of the 14th European Symposium of Artificial Neural Networks, 2006 (ESANN). pdf

Thesis

• G. Leen. PhD Thesis: Context assisted information extraction, University of the West of Scotland, March 2008. pdf