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Given a set of data points drawn from multiple low-dimensional linear subspaces of a high-dimensional space, we consider the problem of clustering these points according to the su...
In Sparse Coding (SC), input vectors are reconstructed using a sparse linear combination of basis vectors. SC has become a popular method for extracting features from data. For a ...
Abstract. We consider the problem of learning an unknown (overcomplete) basis from an unknown sparse linear combination. Introducing the "sparse coding neural gas" algori...
We introduce a new exemplar-based inpainting algorithm that represents the region to be inpainted as a sparse linear combination of example blocks, extracted from the image being ...