Summer School on Sparse Representations and Sparse Coding

Location and Date: Hólar, Iceland, August 15-20, 2010

Sparse modeling is a form of dimensionality reduction which has recently received an increasing amount of attention in several research communities including statistics and machine learning as well as signal analysis and functional analysis. Sparsity is a general tool which can be applied in very different problems such as shape analysis (with applications both on the medical and technical image analysis side), noise removal and inpainting in image processing or compression in signal analysis, to mention a few.

Applications of sparsity in image and signal analysis include a wide range of topics and techniques, such as image reconstruction, image segmentation, super-resolution, compression, linear regression, feature extraction, graphical model learning, sparse PCA, compressive sensing.

Please visit for more details.


Course Credit

3 (+2) ECTS
Three ECTS points are awarded for participation, an additional two points can be achieved by students who do a poster presentation and write a small report on how the topics covered by the summer school can be related to their own PhD project.


The summer school is no longer open for registration.