Summer school in Iceland
On Sparse Representations and Sparse Coding
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.
Topics (to be further specified)
- Introduction to sparse modelling
- Applications within image- and signal processing
The course will consist of lectures given by members of the research groups at IMM-DTU, DIKU and University of Iceland as well as invited speakers with expertise in the field of sparse representations and encoding.
For more information, program and registration go to the Summer school homepage.