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236862Sparse and Redundant Representations and their Applications in Signal and Image Processing
Winter 2019/2020

A MOOC (via EdX) course on sparse representations and their uses in signal and image processing and machine learning. The course covers theoretical aspects of this field (e.g. uniqueness of sparse representation, pursuit performance), practical issues (e.g. dictionary learning, efficient numerical schemes for pursuit), applications in image processing (denoising, inpainting, deblurring, compression), and connection to machine learning topics.