Annual Report 2011

Annual Report 2011

Statistical Machine Learning and Bioinformatics

We develop new efficient computational methods for machine learning, computational inference, and probabilistic modeling. We focus on models for learning from multiple data sources, including multi-view learning, multi-task learning, and multi-way learning, as well as models combining mechanistic and probabilistic approaches. Our primary application areas are computational systems biology and medicine, bioinformatics, proactive information retrieval and multimodal interfaces, as well as brain signal analysis and neuroinformatics.

Contact person: Professor Samuel Kaski
Home page: http://www.hiit.fi/mlb