Date(s) - 01/05/2019
2:00 pm - 4:00 pm
University of Aberdeen
SICSA DVF Professor Juho Rousu will present a 2 hour Master class at the University of Aberdeen on Wednesday 1 May 2019.
Title: Predicting multi-view and structured data with kernel methods
Abstract:During the last two decades, kernel methods – including, but not limited to the celebrated support vector machine – have been extremely succesfull in many walks of life. They continue to be a good alternative to deep neural networks in many real-world applications where data is complex and high-dimensional, and the amount of training data is medium-scale – from hundreds to a few tens of thousands of training examples.
In this masterclass I will focus on how kernel methods can be used for applications where the prediction setup involves heterogeneous or structured data, in particular learning with multiple data sources and predicting structured output.
Short Bio: Juho Rousu is a Professor of Computer Science at Aalto University, Finland. Rousu obtained his PhD in 2001 form University of Helsinki, while working at VTT Technical Centre of Finland. In 2003-2005 he was a Marie Curie Fellow at Royal Holloway University of London. In 2005-2011 he held Lecturer and Professor positions at University of Helsinki, before moving to Aalto University in 2012 where he leads a research group on Kernel Methods, Pattern Analysis and Computational Metabolomics (KEPACO). Rousu’s main research interest is in learning with multiple and structured targets, multiple views and ensembles, with methodological emphasis in regularised learning, kernels and sparsity, as well as efficient convex/non-convex optimisation methods. His applications of interest include metabolomics, biomedicine, pharmacology and synthetic biology.
Professor Rousu is being hosted at the University of Aberdeen by Dr Wei Pang