Roos group teams up with researchers in Turku under an Academy funded 4-year project on Tensor-Based Machine Learning

Wed, 21.06.2017

The Academy of Finland has granted funding for a 4-year project on "Tensor-Based Machine Learning for Big Data with Inherent Dependencies". The funding is awarded to the TensorML consortium consisting of the research groups of Assistant Professor Tapio Pahikkala at the University of Turku and Associate Professor Teemu Roos at HIIT.

Machine learning (ML) has recently achieved a lot in areas where the standard assumptions about the data hold and the amount of training data available is large. However, it still faces many challenges in areas where we would need it the most. The commonly made independently and identically distributed (IID) assumption about data is rarely holds in practice, violating the guarantees about ML methods relying on the assumption. In this project, novel tensor-based ML methods turn the IID violations into our advantage so that both sample complexity and computational complexity are decreased, and the reliability of the prediction performance estimates are improved. Immediate applications include zero-shot learning in general, ML in domains with highly-structured data in particular. The track record of the team leaders, Pahikkala and Roos, in applied research already covers a large array of examples in which the preliminary steps of this research direction has been shown to be highly successful.

More information:

Teemu Roos,
Tapio Pahikkala, tapio(dot)pahikkala(at)utu(dot)fi

Contact person: Teemu Roos

Last updated on 21 Jun 2017 by Teemu Roos - Page created on 21 Jun 2017 by Teemu Roos